catboost_bookrating_v1.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "catboost_bookrating_v1.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "authorship_tag": "ABX9TyOVhSXSe1VQtSC9J5URAujC",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/flydragon2018/Analytics_Vidhya/blob/master/catboost_bookrating_v1.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "u-BYGeLGVWox",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        },
        "outputId": "dce83788-352c-4c64-b4bb-abe02cfe9d57"
      },
      "source": [
        "!nvidia-smi"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "NVIDIA-SMI has failed because it couldn't communicate with the NVIDIA driver. Make sure that the latest NVIDIA driver is installed and running.\n",
            "\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4kDrotL-V_sj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 122
        },
        "outputId": "4adfc571-4435-48fc-9705-f587fe3e58e0"
      },
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive', force_remount=True)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly&response_type=code\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/drive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DbbjQZePV_wB",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 493
        },
        "outputId": "d0b67c39-2a0c-4637-99d8-ac46d8487405"
      },
      "source": [
        "ls drive/\"My Drive\""
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            " 360CC_config.yaml                          mymlabel.tar\n",
            " 5ed0795572319.rar                          mytest.csv\n",
            " 71_OCR_2.zip                               \u001b[0m\u001b[01;34mocr\u001b[0m/\n",
            " 721099_1254334_bundle_archive.zip          \u001b[01;34mocr2\u001b[0m/\n",
            " 75.zip                                     OWN_config.yaml\n",
            " 83_face.zip                                refuse_classification.zip\n",
            " 85book_Rating.zip                          resnet34_sub.csv\n",
            " b7_submission.json                         result.txt\n",
            " book.csv                                   round2label.zip\n",
            " \u001b[01;36mchineseocr\u001b[0m@                                submission.csv\n",
            " chinese_ocr_test0710.py                    \u001b[01;34msurface_defect\u001b[0m/\n",
            " \u001b[01;34mColabNotebooks\u001b[0m/                            test.csv\n",
            "\u001b[01;34m'Colab Notebooks'\u001b[0m/                          test_own.csv\n",
            " colab_train.py                             tf_refuse.zip\n",
            "'Copy of NEU surface defect database.rar'   train.csv\n",
            " \u001b[01;34mdata\u001b[0m/                                      train_myimg627.py\n",
            " data.zip                                   train_myimg.py\n",
            " efficientnet3_sub.csv                      train_own.csv\n",
            " efficientnetb7-60epoch.pkl                 train.py\n",
            " efficientnetb7_sub.csv                     user.csv\n",
            " fastaisubmission.csv                       val.zip\n",
            " keras_textclassify.zip                     yolo-obj_10000.weights\n",
            " mini_train.csv                             yolo-obj_best.weights\n",
            " mini_valid.csv                             \u001b[01;34myolo_ocr\u001b[0m/\n",
            " model.best_model.h5                        \u001b[01;34myolov4\u001b[0m/\n",
            " \u001b[01;34mmovie_rating\u001b[0m/                              yxscaptcha.tar.gz\n",
            " \u001b[01;34mmultilabel\u001b[0m/                                zzl_config.yaml\n",
            " mydata.zip\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "bCMij-iQV_zA",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!unzip -q   /content/drive/\"My Drive\"/85book_Rating.zip  "
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cVkCTMQ7V_8F",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        },
        "outputId": "8b018282-15cc-435c-91f8-960f872472f5"
      },
      "source": [
        "ls"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "book.csv  \u001b[0m\u001b[01;34mdrive\u001b[0m/  \u001b[01;34msample_data\u001b[0m/  test.csv  train.csv  user.csv\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Y-2ZX0iCYODw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "82b0d80d-fa18-4b4f-8f3d-797e890b48af"
      },
      "source": [
        "\n",
        "import pandas as pd\n",
        "\n",
        "\n",
        "traindata = pd.read_csv('train.csv')\n",
        "traindata.head()"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Rating</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>0002005018</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>8</td>\n",
              "      <td>0374157065</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8</td>\n",
              "      <td>0393045218</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>0399135782</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>8</td>\n",
              "      <td>0425176428</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID        ISBN  Book-Rating\n",
              "0        8  0002005018            5\n",
              "1        8  0374157065            0\n",
              "2        8  0393045218            0\n",
              "3        8  0399135782            0\n",
              "4        8  0425176428            0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UhGQQNCmYR45",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 258
        },
        "outputId": "dfa5bc36-97cc-4fa7-8ce9-bfaa97ca830c"
      },
      "source": [
        "books = pd.read_csv(\"book.csv\",encoding='latin-1')\n",
        "books.head()"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/IPython/core/interactiveshell.py:2718: DtypeWarning: Columns (3) have mixed types.Specify dtype option on import or set low_memory=False.\n",
            "  interactivity=interactivity, compiler=compiler, result=result)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0195153448</td>\n",
              "      <td>Classical Mythology</td>\n",
              "      <td>Mark P. O. Morford</td>\n",
              "      <td>2002</td>\n",
              "      <td>Oxford University Press</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0002005018</td>\n",
              "      <td>Clara Callan</td>\n",
              "      <td>Richard Bruce Wright</td>\n",
              "      <td>2001</td>\n",
              "      <td>HarperFlamingo Canada</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0060973129</td>\n",
              "      <td>Decision in Normandy</td>\n",
              "      <td>Carlo D'Este</td>\n",
              "      <td>1991</td>\n",
              "      <td>HarperPerennial</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0374157065</td>\n",
              "      <td>Flu: The Story of the Great Influenza Pandemic...</td>\n",
              "      <td>Gina Bari Kolata</td>\n",
              "      <td>1999</td>\n",
              "      <td>Farrar Straus Giroux</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0393045218</td>\n",
              "      <td>The Mummies of Urumchi</td>\n",
              "      <td>E. J. W. Barber</td>\n",
              "      <td>1999</td>\n",
              "      <td>W. W. Norton &amp; Company</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         ISBN  ...                Publisher\n",
              "0  0195153448  ...  Oxford University Press\n",
              "1  0002005018  ...    HarperFlamingo Canada\n",
              "2  0060973129  ...          HarperPerennial\n",
              "3  0374157065  ...     Farrar Straus Giroux\n",
              "4  0393045218  ...   W. W. Norton & Company\n",
              "\n",
              "[5 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "J02uyaK_Z44J",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49
        },
        "outputId": "939f1c76-7bf8-47ab-d666-8b54b0df9a1c"
      },
      "source": [
        "books.loc[books[\"Year-Of-Publication\"]=='Amit Chaudhuri']"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "Empty DataFrame\n",
              "Columns: [ISBN, Book-Title, Book-Author, Year-Of-Publication, Publisher]\n",
              "Index: []"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IlDtF18IZ5oQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "books.loc[books[\"ISBN\"]=='0330482750', \"Year-Of-Publication\"]=2001\n",
        "books.loc[books[\"ISBN\"]=='0330482750', \"Publisher\"]=\"Pan MacMillan\"\n",
        "books.loc[books[\"ISBN\"]=='0330482750', \"Book-Author\"]=\"Amit Chaudhuri\"\n",
        "books.loc[books[\"ISBN\"]=='0330482750', \"Book-Title\"]=\" A Strange and Sublime Address, Afternoon Raag,Freedom Song\""
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gUo1tvS5YR8d",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "659f5c4f-e1fc-46a0-ffbb-bd9d76f65ff1"
      },
      "source": [
        "userdf = pd.read_csv(\"user.csv\",encoding='latin-1')\n",
        "userdf.head()"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>Location</th>\n",
              "      <th>Age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>nyc, new york, usa</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>stockton, california, usa</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>moscow, yukon territory, russia</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>porto, v.n.gaia, portugal</td>\n",
              "      <td>17.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>farnborough, hants, united kingdom</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID                            Location   Age\n",
              "0        1                  nyc, new york, usa   NaN\n",
              "1        2           stockton, california, usa  18.0\n",
              "2        3     moscow, yukon territory, russia   NaN\n",
              "3        4           porto, v.n.gaia, portugal  17.0\n",
              "4        5  farnborough, hants, united kingdom   NaN"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "PyprDkKfYR_2",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "userdf[\"Age\"]=userdf[\"Age\"].fillna(int(-1))"
      ],
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kij7sGELYSDD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "054a519d-62eb-4880-97de-6939f9207653"
      },
      "source": [
        "traindata = traindata.merge(books,on='ISBN', how='left',suffixes=('_left', '_right'))\n",
        "traindata.head()"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Rating</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>0002005018</td>\n",
              "      <td>5</td>\n",
              "      <td>Clara Callan</td>\n",
              "      <td>Richard Bruce Wright</td>\n",
              "      <td>2001</td>\n",
              "      <td>HarperFlamingo Canada</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>8</td>\n",
              "      <td>0374157065</td>\n",
              "      <td>0</td>\n",
              "      <td>Flu: The Story of the Great Influenza Pandemic...</td>\n",
              "      <td>Gina Bari Kolata</td>\n",
              "      <td>1999</td>\n",
              "      <td>Farrar Straus Giroux</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8</td>\n",
              "      <td>0393045218</td>\n",
              "      <td>0</td>\n",
              "      <td>The Mummies of Urumchi</td>\n",
              "      <td>E. J. W. Barber</td>\n",
              "      <td>1999</td>\n",
              "      <td>W. W. Norton &amp; Company</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>0399135782</td>\n",
              "      <td>0</td>\n",
              "      <td>The Kitchen God's Wife</td>\n",
              "      <td>Amy Tan</td>\n",
              "      <td>1991</td>\n",
              "      <td>Putnam Pub Group</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>8</td>\n",
              "      <td>0425176428</td>\n",
              "      <td>0</td>\n",
              "      <td>What If?: The World's Foremost Military Histor...</td>\n",
              "      <td>Robert Cowley</td>\n",
              "      <td>2000</td>\n",
              "      <td>Berkley Publishing Group</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID        ISBN  ...  Year-Of-Publication                 Publisher\n",
              "0        8  0002005018  ...                 2001     HarperFlamingo Canada\n",
              "1        8  0374157065  ...                 1999      Farrar Straus Giroux\n",
              "2        8  0393045218  ...                 1999    W. W. Norton & Company\n",
              "3        8  0399135782  ...                 1991          Putnam Pub Group\n",
              "4        8  0425176428  ...                 2000  Berkley Publishing Group\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "q7ZkkRysYOHR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "573b4c88-0b96-424a-b355-1e1f05e30cf7"
      },
      "source": [
        "traindata = traindata.merge(userdf,on='User-ID', how='left')\n",
        "traindata.head()"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Rating</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>Location</th>\n",
              "      <th>Age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>0002005018</td>\n",
              "      <td>5</td>\n",
              "      <td>Clara Callan</td>\n",
              "      <td>Richard Bruce Wright</td>\n",
              "      <td>2001</td>\n",
              "      <td>HarperFlamingo Canada</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>8</td>\n",
              "      <td>0374157065</td>\n",
              "      <td>0</td>\n",
              "      <td>Flu: The Story of the Great Influenza Pandemic...</td>\n",
              "      <td>Gina Bari Kolata</td>\n",
              "      <td>1999</td>\n",
              "      <td>Farrar Straus Giroux</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8</td>\n",
              "      <td>0393045218</td>\n",
              "      <td>0</td>\n",
              "      <td>The Mummies of Urumchi</td>\n",
              "      <td>E. J. W. Barber</td>\n",
              "      <td>1999</td>\n",
              "      <td>W. W. Norton &amp; Company</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>0399135782</td>\n",
              "      <td>0</td>\n",
              "      <td>The Kitchen God's Wife</td>\n",
              "      <td>Amy Tan</td>\n",
              "      <td>1991</td>\n",
              "      <td>Putnam Pub Group</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>8</td>\n",
              "      <td>0425176428</td>\n",
              "      <td>0</td>\n",
              "      <td>What If?: The World's Foremost Military Histor...</td>\n",
              "      <td>Robert Cowley</td>\n",
              "      <td>2000</td>\n",
              "      <td>Berkley Publishing Group</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID        ISBN  ...                  Location  Age\n",
              "0        8  0002005018  ...  timmins, ontario, canada -1.0\n",
              "1        8  0374157065  ...  timmins, ontario, canada -1.0\n",
              "2        8  0393045218  ...  timmins, ontario, canada -1.0\n",
              "3        8  0399135782  ...  timmins, ontario, canada -1.0\n",
              "4        8  0425176428  ...  timmins, ontario, canada -1.0\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Vr7m80vwYmlR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "outputId": "190258f6-3fd0-49c5-fa9c-1807c0c5bc6a"
      },
      "source": [
        "traindata.info()"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "Int64Index: 737864 entries, 0 to 737863\n",
            "Data columns (total 9 columns):\n",
            " #   Column               Non-Null Count   Dtype  \n",
            "---  ------               --------------   -----  \n",
            " 0   User-ID              737864 non-null  int64  \n",
            " 1   ISBN                 737864 non-null  object \n",
            " 2   Book-Rating          737864 non-null  int64  \n",
            " 3   Book-Title           737864 non-null  object \n",
            " 4   Book-Author          737863 non-null  object \n",
            " 5   Year-Of-Publication  737864 non-null  object \n",
            " 6   Publisher            737863 non-null  object \n",
            " 7   Location             737864 non-null  object \n",
            " 8   Age                  737864 non-null  float64\n",
            "dtypes: float64(1), int64(2), object(6)\n",
            "memory usage: 56.3+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2wGeNv7wYmot",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "traindata.to_csv(\"mybook_train.csv\",index=None)"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ydWqUGV9Ymrs",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "7b9e4ebd-ff6a-4586-eb58-9e1f974813e8"
      },
      "source": [
        "testdata = pd.read_csv('test.csv')\n",
        "testdata.head()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0060973129</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>0671870432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>074322678X</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>8</td>\n",
              "      <td>0771074670</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>14</td>\n",
              "      <td>0689821166</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  User-ID        ISBN\n",
              "0   0        8  0060973129\n",
              "1   1        8  0671870432\n",
              "2   2        8  074322678X\n",
              "3   3        8  0771074670\n",
              "4   4       14  0689821166"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 39
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IE7kgsDIYmu8",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "c5914beb-4370-484d-a97e-dbceb603b936"
      },
      "source": [
        "testdata = testdata.merge(books,on='ISBN', how='left',suffixes=('_left', '_right'))\n",
        "testdata.head()"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0060973129</td>\n",
              "      <td>Decision in Normandy</td>\n",
              "      <td>Carlo D'Este</td>\n",
              "      <td>1991</td>\n",
              "      <td>HarperPerennial</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>0671870432</td>\n",
              "      <td>PLEADING GUILTY</td>\n",
              "      <td>Scott Turow</td>\n",
              "      <td>1993</td>\n",
              "      <td>Audioworks</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>074322678X</td>\n",
              "      <td>Where You'll Find Me: And Other Stories</td>\n",
              "      <td>Ann Beattie</td>\n",
              "      <td>2002</td>\n",
              "      <td>Scribner</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>8</td>\n",
              "      <td>0771074670</td>\n",
              "      <td>Nights Below Station Street</td>\n",
              "      <td>David Adams Richards</td>\n",
              "      <td>1988</td>\n",
              "      <td>Emblem Editions</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>14</td>\n",
              "      <td>0689821166</td>\n",
              "      <td>Flood : Mississippi 1927</td>\n",
              "      <td>Kathleen Duey</td>\n",
              "      <td>1998</td>\n",
              "      <td>Aladdin</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  User-ID  ... Year-Of-Publication        Publisher\n",
              "0   0        8  ...                1991  HarperPerennial\n",
              "1   1        8  ...                1993       Audioworks\n",
              "2   2        8  ...                2002         Scribner\n",
              "3   3        8  ...                1988  Emblem Editions\n",
              "4   4       14  ...                1998          Aladdin\n",
              "\n",
              "[5 rows x 7 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RQ34QoJCYmxk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "6e54ceb6-0774-4d0f-9ecd-b15bc91e822d"
      },
      "source": [
        "testdata = testdata.merge(userdf,on='User-ID', how='left')\n",
        "testdata.head()"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>Location</th>\n",
              "      <th>Age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0060973129</td>\n",
              "      <td>Decision in Normandy</td>\n",
              "      <td>Carlo D'Este</td>\n",
              "      <td>1991</td>\n",
              "      <td>HarperPerennial</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>0671870432</td>\n",
              "      <td>PLEADING GUILTY</td>\n",
              "      <td>Scott Turow</td>\n",
              "      <td>1993</td>\n",
              "      <td>Audioworks</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>074322678X</td>\n",
              "      <td>Where You'll Find Me: And Other Stories</td>\n",
              "      <td>Ann Beattie</td>\n",
              "      <td>2002</td>\n",
              "      <td>Scribner</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>8</td>\n",
              "      <td>0771074670</td>\n",
              "      <td>Nights Below Station Street</td>\n",
              "      <td>David Adams Richards</td>\n",
              "      <td>1988</td>\n",
              "      <td>Emblem Editions</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>14</td>\n",
              "      <td>0689821166</td>\n",
              "      <td>Flood : Mississippi 1927</td>\n",
              "      <td>Kathleen Duey</td>\n",
              "      <td>1998</td>\n",
              "      <td>Aladdin</td>\n",
              "      <td>mediapolis, iowa, usa</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  User-ID        ISBN  ...        Publisher                  Location  Age\n",
              "0   0        8  0060973129  ...  HarperPerennial  timmins, ontario, canada -1.0\n",
              "1   1        8  0671870432  ...       Audioworks  timmins, ontario, canada -1.0\n",
              "2   2        8  074322678X  ...         Scribner  timmins, ontario, canada -1.0\n",
              "3   3        8  0771074670  ...  Emblem Editions  timmins, ontario, canada -1.0\n",
              "4   4       14  0689821166  ...          Aladdin     mediapolis, iowa, usa -1.0\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Mi6livz-Ym0b",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "testdata.to_csv(\"mybook_test.csv\",index=None)"
      ],
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3S81h5sTZXl3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170
        },
        "outputId": "48fb65e8-3243-4cbc-b66d-1a49e53db588"
      },
      "source": [
        "list(traindata.columns.values)"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['User-ID',\n",
              " 'ISBN',\n",
              " 'Book-Rating',\n",
              " 'Book-Title',\n",
              " 'Book-Author',\n",
              " 'Year-Of-Publication',\n",
              " 'Publisher',\n",
              " 'Location',\n",
              " 'Age']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GB5LGq1LZXph",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170
        },
        "outputId": "2545d184-895b-48d9-a193-a3820f122df1"
      },
      "source": [
        "list(testdata)"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['id',\n",
              " 'User-ID',\n",
              " 'ISBN',\n",
              " 'Book-Title',\n",
              " 'Book-Author',\n",
              " 'Year-Of-Publication',\n",
              " 'Publisher',\n",
              " 'Location',\n",
              " 'Age']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 44
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BzeRi7D9ZXtl",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "bfff4ef4-a1af-4992-8cb1-99274b0e6a55"
      },
      "source": [
        "traindf=pd.read_csv(\"mybook_train.csv\")\n",
        "traindf.head()"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Rating</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>Location</th>\n",
              "      <th>Age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>0002005018</td>\n",
              "      <td>5</td>\n",
              "      <td>Clara Callan</td>\n",
              "      <td>Richard Bruce Wright</td>\n",
              "      <td>2001</td>\n",
              "      <td>HarperFlamingo Canada</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>8</td>\n",
              "      <td>0374157065</td>\n",
              "      <td>0</td>\n",
              "      <td>Flu: The Story of the Great Influenza Pandemic...</td>\n",
              "      <td>Gina Bari Kolata</td>\n",
              "      <td>1999</td>\n",
              "      <td>Farrar Straus Giroux</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8</td>\n",
              "      <td>0393045218</td>\n",
              "      <td>0</td>\n",
              "      <td>The Mummies of Urumchi</td>\n",
              "      <td>E. J. W. Barber</td>\n",
              "      <td>1999</td>\n",
              "      <td>W. W. Norton &amp; Company</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>0399135782</td>\n",
              "      <td>0</td>\n",
              "      <td>The Kitchen God's Wife</td>\n",
              "      <td>Amy Tan</td>\n",
              "      <td>1991</td>\n",
              "      <td>Putnam Pub Group</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>8</td>\n",
              "      <td>0425176428</td>\n",
              "      <td>0</td>\n",
              "      <td>What If?: The World's Foremost Military Histor...</td>\n",
              "      <td>Robert Cowley</td>\n",
              "      <td>2000</td>\n",
              "      <td>Berkley Publishing Group</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID        ISBN  ...                  Location  Age\n",
              "0        8  0002005018  ...  timmins, ontario, canada -1.0\n",
              "1        8  0374157065  ...  timmins, ontario, canada -1.0\n",
              "2        8  0393045218  ...  timmins, ontario, canada -1.0\n",
              "3        8  0399135782  ...  timmins, ontario, canada -1.0\n",
              "4        8  0425176428  ...  timmins, ontario, canada -1.0\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ug3qHvOeYm3a",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "outputId": "30043b0b-c6d7-4c31-ee49-39f9446a4591"
      },
      "source": [
        "traindf.info()"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 737864 entries, 0 to 737863\n",
            "Data columns (total 9 columns):\n",
            " #   Column               Non-Null Count   Dtype  \n",
            "---  ------               --------------   -----  \n",
            " 0   User-ID              737864 non-null  int64  \n",
            " 1   ISBN                 737864 non-null  object \n",
            " 2   Book-Rating          737864 non-null  int64  \n",
            " 3   Book-Title           737864 non-null  object \n",
            " 4   Book-Author          737863 non-null  object \n",
            " 5   Year-Of-Publication  737864 non-null  int64  \n",
            " 6   Publisher            737863 non-null  object \n",
            " 7   Location             737864 non-null  object \n",
            " 8   Age                  737864 non-null  float64\n",
            "dtypes: float64(1), int64(3), object(5)\n",
            "memory usage: 50.7+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1dPuHpKFYm8_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "c4dfc143-afbb-49fb-d9c3-dc76ff683e6f"
      },
      "source": [
        "testdf=pd.read_csv(\"mybook_test.csv\")\n",
        "testdf.head()"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>id</th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>Location</th>\n",
              "      <th>Age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>8</td>\n",
              "      <td>0060973129</td>\n",
              "      <td>Decision in Normandy</td>\n",
              "      <td>Carlo D'Este</td>\n",
              "      <td>1991</td>\n",
              "      <td>HarperPerennial</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "      <td>0671870432</td>\n",
              "      <td>PLEADING GUILTY</td>\n",
              "      <td>Scott Turow</td>\n",
              "      <td>1993</td>\n",
              "      <td>Audioworks</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>074322678X</td>\n",
              "      <td>Where You'll Find Me: And Other Stories</td>\n",
              "      <td>Ann Beattie</td>\n",
              "      <td>2002</td>\n",
              "      <td>Scribner</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>8</td>\n",
              "      <td>0771074670</td>\n",
              "      <td>Nights Below Station Street</td>\n",
              "      <td>David Adams Richards</td>\n",
              "      <td>1988</td>\n",
              "      <td>Emblem Editions</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>14</td>\n",
              "      <td>0689821166</td>\n",
              "      <td>Flood : Mississippi 1927</td>\n",
              "      <td>Kathleen Duey</td>\n",
              "      <td>1998</td>\n",
              "      <td>Aladdin</td>\n",
              "      <td>mediapolis, iowa, usa</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   id  User-ID        ISBN  ...        Publisher                  Location  Age\n",
              "0   0        8  0060973129  ...  HarperPerennial  timmins, ontario, canada -1.0\n",
              "1   1        8  0671870432  ...       Audioworks  timmins, ontario, canada -1.0\n",
              "2   2        8  074322678X  ...         Scribner  timmins, ontario, canada -1.0\n",
              "3   3        8  0771074670  ...  Emblem Editions  timmins, ontario, canada -1.0\n",
              "4   4       14  0689821166  ...          Aladdin     mediapolis, iowa, usa -1.0\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hsXfTpsfbCCg",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "afd622f0-4f7a-4e0b-abb5-7abe73df03b9"
      },
      "source": [
        "test=testdf.drop(\"id\",axis=1)\n",
        "test.head()"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>User-ID</th>\n",
              "      <th>ISBN</th>\n",
              "      <th>Book-Title</th>\n",
              "      <th>Book-Author</th>\n",
              "      <th>Year-Of-Publication</th>\n",
              "      <th>Publisher</th>\n",
              "      <th>Location</th>\n",
              "      <th>Age</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>0060973129</td>\n",
              "      <td>Decision in Normandy</td>\n",
              "      <td>Carlo D'Este</td>\n",
              "      <td>1991</td>\n",
              "      <td>HarperPerennial</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>8</td>\n",
              "      <td>0671870432</td>\n",
              "      <td>PLEADING GUILTY</td>\n",
              "      <td>Scott Turow</td>\n",
              "      <td>1993</td>\n",
              "      <td>Audioworks</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>8</td>\n",
              "      <td>074322678X</td>\n",
              "      <td>Where You'll Find Me: And Other Stories</td>\n",
              "      <td>Ann Beattie</td>\n",
              "      <td>2002</td>\n",
              "      <td>Scribner</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>8</td>\n",
              "      <td>0771074670</td>\n",
              "      <td>Nights Below Station Street</td>\n",
              "      <td>David Adams Richards</td>\n",
              "      <td>1988</td>\n",
              "      <td>Emblem Editions</td>\n",
              "      <td>timmins, ontario, canada</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>14</td>\n",
              "      <td>0689821166</td>\n",
              "      <td>Flood : Mississippi 1927</td>\n",
              "      <td>Kathleen Duey</td>\n",
              "      <td>1998</td>\n",
              "      <td>Aladdin</td>\n",
              "      <td>mediapolis, iowa, usa</td>\n",
              "      <td>-1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   User-ID        ISBN  ...                  Location  Age\n",
              "0        8  0060973129  ...  timmins, ontario, canada -1.0\n",
              "1        8  0671870432  ...  timmins, ontario, canada -1.0\n",
              "2        8  074322678X  ...  timmins, ontario, canada -1.0\n",
              "3        8  0771074670  ...  timmins, ontario, canada -1.0\n",
              "4       14  0689821166  ...     mediapolis, iowa, usa -1.0\n",
              "\n",
              "[5 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tzHQ8aiZbYHR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 343
        },
        "outputId": "fb17b268-eab9-4106-ad2a-ad785aa352cf"
      },
      "source": [
        "!pip install catboost"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting catboost\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/96/6c/6608210b29649267de52001b09e369777ee2a5cfe1c71fa75eba82a4f2dc/catboost-0.24-cp36-none-manylinux1_x86_64.whl (65.9MB)\n",
            "\u001b[K     |████████████████████████████████| 65.9MB 65kB/s \n",
            "\u001b[?25hRequirement already satisfied: scipy in /usr/local/lib/python3.6/dist-packages (from catboost) (1.4.1)\n",
            "Requirement already satisfied: matplotlib in /usr/local/lib/python3.6/dist-packages (from catboost) (3.2.2)\n",
            "Requirement already satisfied: graphviz in /usr/local/lib/python3.6/dist-packages (from catboost) (0.10.1)\n",
            "Requirement already satisfied: plotly in /usr/local/lib/python3.6/dist-packages (from catboost) (4.4.1)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.6/dist-packages (from catboost) (1.15.0)\n",
            "Requirement already satisfied: pandas>=0.24.0 in /usr/local/lib/python3.6/dist-packages (from catboost) (1.0.5)\n",
            "Requirement already satisfied: numpy>=1.16.0 in /usr/local/lib/python3.6/dist-packages (from catboost) (1.18.5)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->catboost) (1.2.0)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->catboost) (2.8.1)\n",
            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->catboost) (2.4.7)\n",
            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.6/dist-packages (from matplotlib->catboost) (0.10.0)\n",
            "Requirement already satisfied: retrying>=1.3.3 in /usr/local/lib/python3.6/dist-packages (from plotly->catboost) (1.3.3)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.6/dist-packages (from pandas>=0.24.0->catboost) (2018.9)\n",
            "Installing collected packages: catboost\n",
            "Successfully installed catboost-0.24\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "p8DZpvwjbYLd",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NEm2KRF7bCKX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "catX = traindf.drop(['Book-Rating'], axis = 1)"
      ],
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7a8b-Sy4bCNw",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272
        },
        "outputId": "f035d56b-9892-45ec-8647-7911e7e481a2"
      },
      "source": [
        "catX.info()"
      ],
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 737864 entries, 0 to 737863\n",
            "Data columns (total 8 columns):\n",
            " #   Column               Non-Null Count   Dtype  \n",
            "---  ------               --------------   -----  \n",
            " 0   User-ID              737864 non-null  int64  \n",
            " 1   ISBN                 737864 non-null  object \n",
            " 2   Book-Title           737864 non-null  object \n",
            " 3   Book-Author          737863 non-null  object \n",
            " 4   Year-Of-Publication  737864 non-null  int64  \n",
            " 5   Publisher            737863 non-null  object \n",
            " 6   Location             737864 non-null  object \n",
            " 7   Age                  737864 non-null  float64\n",
            "dtypes: float64(1), int64(2), object(5)\n",
            "memory usage: 45.0+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NZvLu8sXbCQl",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "caty=traindf['Book-Rating'] "
      ],
      "execution_count": 56,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uCoZCMxLbCT4",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "catX[\"ISBN\"]=catX[\"ISBN\"].astype(str)\n",
        "catX[\"Book-Title\"]=catX[\"Book-Title\"].astype(str)\n",
        "catX[\"Book-Author\"]=catX[\"Book-Author\"].astype(str)\n",
        "catX[\"Publisher\"]=catX[\"Publisher\"].astype(str)\n",
        "catX[\"Location\"]=catX[\"Location\"].astype(str)\n",
        "catX[\"Year-Of-Publication\"]=catX[\"Year-Of-Publication\"].astype(int)   "
      ],
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-wB983NqbCWz",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "testX=test"
      ],
      "execution_count": 60,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZtU42tyybCaG",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 272
        },
        "outputId": "97a04406-1add-4e44-8e77-1fa6aa64de83"
      },
      "source": [
        "testX.info()"
      ],
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 206235 entries, 0 to 206234\n",
            "Data columns (total 8 columns):\n",
            " #   Column               Non-Null Count   Dtype  \n",
            "---  ------               --------------   -----  \n",
            " 0   User-ID              206235 non-null  int64  \n",
            " 1   ISBN                 206235 non-null  object \n",
            " 2   Book-Title           206235 non-null  object \n",
            " 3   Book-Author          206235 non-null  object \n",
            " 4   Year-Of-Publication  206235 non-null  int64  \n",
            " 5   Publisher            206234 non-null  object \n",
            " 6   Location             206235 non-null  object \n",
            " 7   Age                  206235 non-null  float64\n",
            "dtypes: float64(1), int64(2), object(5)\n",
            "memory usage: 12.6+ MB\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EnRsa9FkbCda",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "testX[\"ISBN\"]=testX[\"ISBN\"].astype(str)\n",
        "testX[\"Book-Title\"]=testX[\"Book-Title\"].astype(str)\n",
        "testX[\"Book-Author\"]=testX[\"Book-Author\"].astype(str)\n",
        "testX[\"Publisher\"]=testX[\"Publisher\"].astype(str)\n",
        "testX[\"Location\"]=testX[\"Location\"].astype(str)\n",
        "testX[\"Year-Of-Publication\"]=testX[\"Year-Of-Publication\"].astype(int)  "
      ],
      "execution_count": 63,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "un03qCpUYm_u",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "1b2a90af-d38a-447e-82ef-6b99572ebe1b"
      },
      "source": [
        "from catboost import CatBoostClassifier\n",
        "\n",
        "\n",
        "# Initialize CatBoostClassifier\n",
        "model = CatBoostClassifier()\n",
        "cat_features =['ISBN','Book-Title','Book-Author', 'Publisher', 'Location']\n",
        "\n",
        "\n",
        "# Fit model\n",
        "model.fit(catX, caty, cat_features)\n",
        "# Get predicted classes\n",
        "preds_class = model.predict(testX)\n",
        "print(preds_class)\n",
        "\n",
        "p=preds_class\n",
        "result=[]\n",
        "for k in range(len(p)):\n",
        "    #print(k,p[k])\n",
        "    result.append([k,p[k].numpy()])\n",
        "submit=pd.DataFrame(result)\n",
        "submit.to_csv(\"cat_np_submission.csv\",index=None,header=None)\n"
      ],
      "execution_count": 64,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Learning rate set to 0.110813\n",
            "0:\tlearn: 1.9488214\ttotal: 23.9s\tremaining: 6h 38m 44s\n",
            "1:\tlearn: 1.7643316\ttotal: 47.2s\tremaining: 6h 32m 53s\n",
            "2:\tlearn: 1.6453567\ttotal: 1m 10s\tremaining: 6h 27m 45s\n",
            "3:\tlearn: 1.5600784\ttotal: 1m 33s\tremaining: 6h 29m 2s\n",
            "4:\tlearn: 1.4955967\ttotal: 1m 55s\tremaining: 6h 24m 9s\n",
            "5:\tlearn: 1.4447590\ttotal: 2m 18s\tremaining: 6h 21m 22s\n",
            "6:\tlearn: 1.4035243\ttotal: 2m 41s\tremaining: 6h 20m 59s\n",
            "7:\tlearn: 1.3696466\ttotal: 3m 3s\tremaining: 6h 18m 44s\n",
            "8:\tlearn: 1.3410057\ttotal: 3m 33s\tremaining: 6h 31m 11s\n",
            "9:\tlearn: 1.3174180\ttotal: 3m 58s\tremaining: 6h 33m 49s\n",
            "10:\tlearn: 1.2968471\ttotal: 4m 29s\tremaining: 6h 44m 1s\n",
            "11:\tlearn: 1.2801384\ttotal: 4m 56s\tremaining: 6h 47m 25s\n",
            "12:\tlearn: 1.2657919\ttotal: 5m 24s\tremaining: 6h 50m 8s\n",
            "13:\tlearn: 1.2536680\ttotal: 5m 51s\tremaining: 6h 52m 21s\n",
            "14:\tlearn: 1.2430445\ttotal: 6m 21s\tremaining: 6h 57m 52s\n",
            "15:\tlearn: 1.2334854\ttotal: 6m 52s\tremaining: 7h 2m 52s\n",
            "16:\tlearn: 1.2256563\ttotal: 7m 20s\tremaining: 7h 4m 19s\n",
            "17:\tlearn: 1.2179502\ttotal: 7m 48s\tremaining: 7h 6m 15s\n",
            "18:\tlearn: 1.2118268\ttotal: 8m 10s\tremaining: 7h 2m 29s\n",
            "19:\tlearn: 1.2059343\ttotal: 8m 37s\tremaining: 7h 2m 30s\n",
            "20:\tlearn: 1.2008775\ttotal: 9m 3s\tremaining: 7h 2m 15s\n",
            "21:\tlearn: 1.1923198\ttotal: 9m 31s\tremaining: 7h 3m 25s\n",
            "22:\tlearn: 1.1858404\ttotal: 9m 59s\tremaining: 7h 4m 11s\n",
            "23:\tlearn: 1.1803489\ttotal: 10m 26s\tremaining: 7h 4m 55s\n",
            "24:\tlearn: 1.1759609\ttotal: 10m 54s\tremaining: 7h 5m 20s\n",
            "25:\tlearn: 1.1722565\ttotal: 11m 22s\tremaining: 7h 6m 21s\n",
            "26:\tlearn: 1.1692035\ttotal: 11m 54s\tremaining: 7h 9m 2s\n",
            "27:\tlearn: 1.1667374\ttotal: 12m 21s\tremaining: 7h 9m\n",
            "28:\tlearn: 1.1643858\ttotal: 12m 49s\tremaining: 7h 9m 25s\n",
            "29:\tlearn: 1.1625765\ttotal: 13m 18s\tremaining: 7h 10m 7s\n",
            "30:\tlearn: 1.1607048\ttotal: 13m 47s\tremaining: 7h 10m 56s\n",
            "31:\tlearn: 1.1592102\ttotal: 14m 14s\tremaining: 7h 10m 48s\n",
            "32:\tlearn: 1.1573359\ttotal: 14m 42s\tremaining: 7h 10m 51s\n",
            "33:\tlearn: 1.1555072\ttotal: 15m 9s\tremaining: 7h 10m 41s\n",
            "34:\tlearn: 1.1539987\ttotal: 15m 38s\tremaining: 7h 11m 26s\n",
            "35:\tlearn: 1.1529511\ttotal: 16m 6s\tremaining: 7h 11m 18s\n",
            "36:\tlearn: 1.1521350\ttotal: 16m 36s\tremaining: 7h 12m 13s\n",
            "37:\tlearn: 1.1511416\ttotal: 17m 4s\tremaining: 7h 12m 10s\n",
            "38:\tlearn: 1.1501114\ttotal: 17m 34s\tremaining: 7h 13m 11s\n",
            "39:\tlearn: 1.1489272\ttotal: 18m 14s\tremaining: 7h 17m 46s\n",
            "40:\tlearn: 1.1476147\ttotal: 18m 53s\tremaining: 7h 21m 54s\n",
            "41:\tlearn: 1.1468963\ttotal: 19m 26s\tremaining: 7h 23m 25s\n",
            "42:\tlearn: 1.1461455\ttotal: 19m 53s\tremaining: 7h 22m 52s\n",
            "43:\tlearn: 1.1454901\ttotal: 20m 24s\tremaining: 7h 23m 23s\n",
            "44:\tlearn: 1.1448916\ttotal: 21m 1s\tremaining: 7h 26m 12s\n",
            "45:\tlearn: 1.1443347\ttotal: 21m 35s\tremaining: 7h 27m 38s\n",
            "46:\tlearn: 1.1438870\ttotal: 22m 3s\tremaining: 7h 27m 18s\n",
            "47:\tlearn: 1.1429354\ttotal: 22m 41s\tremaining: 7h 29m 55s\n",
            "48:\tlearn: 1.1419297\ttotal: 23m 18s\tremaining: 7h 32m 19s\n",
            "49:\tlearn: 1.1414080\ttotal: 23m 49s\tremaining: 7h 32m 48s\n",
            "50:\tlearn: 1.1408323\ttotal: 24m 22s\tremaining: 7h 33m 33s\n",
            "51:\tlearn: 1.1403857\ttotal: 24m 54s\tremaining: 7h 34m 12s\n",
            "52:\tlearn: 1.1398778\ttotal: 25m 22s\tremaining: 7h 33m 19s\n",
            "53:\tlearn: 1.1394330\ttotal: 25m 54s\tremaining: 7h 33m 45s\n",
            "54:\tlearn: 1.1390695\ttotal: 26m 26s\tremaining: 7h 34m 24s\n",
            "55:\tlearn: 1.1386339\ttotal: 27m 1s\tremaining: 7h 35m 30s\n",
            "56:\tlearn: 1.1382491\ttotal: 27m 34s\tremaining: 7h 36m 16s\n",
            "57:\tlearn: 1.1378008\ttotal: 28m 15s\tremaining: 7h 38m 57s\n",
            "58:\tlearn: 1.1374291\ttotal: 28m 44s\tremaining: 7h 38m 23s\n",
            "59:\tlearn: 1.1371968\ttotal: 29m 16s\tremaining: 7h 38m 43s\n",
            "60:\tlearn: 1.1368577\ttotal: 29m 47s\tremaining: 7h 38m 41s\n",
            "61:\tlearn: 1.1366099\ttotal: 30m 19s\tremaining: 7h 38m 42s\n",
            "62:\tlearn: 1.1363563\ttotal: 30m 48s\tremaining: 7h 38m 15s\n",
            "63:\tlearn: 1.1361103\ttotal: 31m 18s\tremaining: 7h 37m 47s\n",
            "64:\tlearn: 1.1358613\ttotal: 31m 52s\tremaining: 7h 38m 24s\n",
            "65:\tlearn: 1.1355312\ttotal: 32m 23s\tremaining: 7h 38m 17s\n",
            "66:\tlearn: 1.1347815\ttotal: 33m\tremaining: 7h 39m 37s\n",
            "67:\tlearn: 1.1339879\ttotal: 33m 36s\tremaining: 7h 40m 37s\n",
            "68:\tlearn: 1.1333409\ttotal: 34m 15s\tremaining: 7h 42m 7s\n",
            "69:\tlearn: 1.1331613\ttotal: 34m 48s\tremaining: 7h 42m 25s\n",
            "70:\tlearn: 1.1327441\ttotal: 35m 24s\tremaining: 7h 43m 12s\n",
            "71:\tlearn: 1.1323593\ttotal: 36m 2s\tremaining: 7h 44m 29s\n",
            "72:\tlearn: 1.1315021\ttotal: 36m 39s\tremaining: 7h 45m 35s\n",
            "73:\tlearn: 1.1313008\ttotal: 37m 16s\tremaining: 7h 46m 24s\n",
            "74:\tlearn: 1.1310620\ttotal: 37m 49s\tremaining: 7h 46m 32s\n",
            "75:\tlearn: 1.1303088\ttotal: 38m 27s\tremaining: 7h 47m 37s\n",
            "76:\tlearn: 1.1300662\ttotal: 38m 57s\tremaining: 7h 47m 1s\n",
            "77:\tlearn: 1.1298905\ttotal: 39m 29s\tremaining: 7h 46m 50s\n",
            "78:\tlearn: 1.1296165\ttotal: 40m 11s\tremaining: 7h 48m 31s\n",
            "79:\tlearn: 1.1294058\ttotal: 40m 45s\tremaining: 7h 48m 45s\n",
            "80:\tlearn: 1.1289540\ttotal: 41m 23s\tremaining: 7h 49m 37s\n",
            "81:\tlearn: 1.1287645\ttotal: 41m 51s\tremaining: 7h 48m 40s\n",
            "82:\tlearn: 1.1286274\ttotal: 42m 24s\tremaining: 7h 48m 35s\n",
            "83:\tlearn: 1.1277570\ttotal: 43m 1s\tremaining: 7h 49m 15s\n",
            "84:\tlearn: 1.1274784\ttotal: 43m 36s\tremaining: 7h 49m 29s\n",
            "85:\tlearn: 1.1271562\ttotal: 44m 11s\tremaining: 7h 49m 34s\n",
            "86:\tlearn: 1.1270184\ttotal: 44m 44s\tremaining: 7h 49m 35s\n",
            "87:\tlearn: 1.1259976\ttotal: 45m 23s\tremaining: 7h 50m 27s\n",
            "88:\tlearn: 1.1258419\ttotal: 45m 58s\tremaining: 7h 50m 39s\n",
            "89:\tlearn: 1.1255632\ttotal: 46m 39s\tremaining: 7h 51m 48s\n",
            "90:\tlearn: 1.1253020\ttotal: 47m 22s\tremaining: 7h 53m 10s\n",
            "91:\tlearn: 1.1247662\ttotal: 48m 1s\tremaining: 7h 53m 57s\n",
            "92:\tlearn: 1.1245767\ttotal: 48m 29s\tremaining: 7h 52m 58s\n",
            "93:\tlearn: 1.1244067\ttotal: 49m 3s\tremaining: 7h 52m 49s\n",
            "94:\tlearn: 1.1242565\ttotal: 49m 39s\tremaining: 7h 53m 3s\n",
            "95:\tlearn: 1.1239549\ttotal: 50m 19s\tremaining: 7h 53m 49s\n",
            "96:\tlearn: 1.1233099\ttotal: 50m 57s\tremaining: 7h 54m 21s\n",
            "97:\tlearn: 1.1230315\ttotal: 51m 34s\tremaining: 7h 54m 45s\n",
            "98:\tlearn: 1.1228738\ttotal: 52m 4s\tremaining: 7h 53m 57s\n",
            "99:\tlearn: 1.1223794\ttotal: 52m 42s\tremaining: 7h 54m 21s\n",
            "100:\tlearn: 1.1219909\ttotal: 53m 20s\tremaining: 7h 54m 49s\n",
            "101:\tlearn: 1.1218493\ttotal: 53m 53s\tremaining: 7h 54m 27s\n",
            "102:\tlearn: 1.1215585\ttotal: 54m 31s\tremaining: 7h 54m 47s\n",
            "103:\tlearn: 1.1214372\ttotal: 55m 4s\tremaining: 7h 54m 26s\n",
            "104:\tlearn: 1.1211345\ttotal: 55m 42s\tremaining: 7h 54m 52s\n",
            "105:\tlearn: 1.1208899\ttotal: 56m 20s\tremaining: 7h 55m 10s\n",
            "106:\tlearn: 1.1206922\ttotal: 56m 48s\tremaining: 7h 54m 6s\n",
            "107:\tlearn: 1.1205688\ttotal: 57m 23s\tremaining: 7h 53m 58s\n",
            "108:\tlearn: 1.1203594\ttotal: 58m 3s\tremaining: 7h 54m 37s\n",
            "109:\tlearn: 1.1202994\ttotal: 58m 37s\tremaining: 7h 54m 18s\n",
            "110:\tlearn: 1.1201729\ttotal: 59m 10s\tremaining: 7h 53m 57s\n",
            "111:\tlearn: 1.1200485\ttotal: 59m 49s\tremaining: 7h 54m 20s\n",
            "112:\tlearn: 1.1195598\ttotal: 1h 27s\tremaining: 7h 54m 31s\n",
            "113:\tlearn: 1.1193914\ttotal: 1h 52s\tremaining: 7h 53m 4s\n",
            "114:\tlearn: 1.1192788\ttotal: 1h 1m 26s\tremaining: 7h 52m 48s\n",
            "115:\tlearn: 1.1190351\ttotal: 1h 2m 6s\tremaining: 7h 53m 20s\n",
            "116:\tlearn: 1.1187990\ttotal: 1h 2m 48s\tremaining: 7h 53m 57s\n",
            "117:\tlearn: 1.1187009\ttotal: 1h 3m 23s\tremaining: 7h 53m 46s\n",
            "118:\tlearn: 1.1185427\ttotal: 1h 3m 55s\tremaining: 7h 53m 18s\n",
            "119:\tlearn: 1.1182934\ttotal: 1h 4m 36s\tremaining: 7h 53m 47s\n",
            "120:\tlearn: 1.1179479\ttotal: 1h 5m 14s\tremaining: 7h 53m 57s\n",
            "121:\tlearn: 1.1178481\ttotal: 1h 5m 47s\tremaining: 7h 53m 30s\n",
            "122:\tlearn: 1.1175945\ttotal: 1h 6m 25s\tremaining: 7h 53m 36s\n",
            "123:\tlearn: 1.1173506\ttotal: 1h 7m 5s\tremaining: 7h 53m 59s\n",
            "124:\tlearn: 1.1169631\ttotal: 1h 7m 45s\tremaining: 7h 54m 15s\n",
            "125:\tlearn: 1.1168184\ttotal: 1h 8m 13s\tremaining: 7h 53m 12s\n",
            "126:\tlearn: 1.1167222\ttotal: 1h 8m 44s\tremaining: 7h 52m 32s\n",
            "127:\tlearn: 1.1165914\ttotal: 1h 9m 17s\tremaining: 7h 52m\n",
            "128:\tlearn: 1.1164515\ttotal: 1h 9m 50s\tremaining: 7h 51m 34s\n",
            "129:\tlearn: 1.1162054\ttotal: 1h 10m 25s\tremaining: 7h 51m 17s\n",
            "130:\tlearn: 1.1159131\ttotal: 1h 10m 53s\tremaining: 7h 50m 17s\n",
            "131:\tlearn: 1.1157744\ttotal: 1h 11m 27s\tremaining: 7h 49m 55s\n",
            "132:\tlearn: 1.1154902\ttotal: 1h 12m 6s\tremaining: 7h 50m 2s\n",
            "133:\tlearn: 1.1152959\ttotal: 1h 12m 44s\tremaining: 7h 50m 7s\n",
            "134:\tlearn: 1.1151878\ttotal: 1h 13m 15s\tremaining: 7h 49m 23s\n",
            "135:\tlearn: 1.1150726\ttotal: 1h 13m 43s\tremaining: 7h 48m 20s\n",
            "136:\tlearn: 1.1146599\ttotal: 1h 14m 21s\tremaining: 7h 48m 21s\n",
            "137:\tlearn: 1.1141828\ttotal: 1h 15m 2s\tremaining: 7h 48m 44s\n",
            "138:\tlearn: 1.1140626\ttotal: 1h 15m 36s\tremaining: 7h 48m 17s\n",
            "139:\tlearn: 1.1138704\ttotal: 1h 16m 15s\tremaining: 7h 48m 27s\n",
            "140:\tlearn: 1.1135570\ttotal: 1h 16m 45s\tremaining: 7h 47m 37s\n",
            "141:\tlearn: 1.1134329\ttotal: 1h 17m 13s\tremaining: 7h 46m 35s\n",
            "142:\tlearn: 1.1131793\ttotal: 1h 17m 45s\tremaining: 7h 45m 58s\n",
            "143:\tlearn: 1.1127204\ttotal: 1h 18m 26s\tremaining: 7h 46m 18s\n",
            "144:\tlearn: 1.1126313\ttotal: 1h 19m 5s\tremaining: 7h 46m 21s\n",
            "145:\tlearn: 1.1125289\ttotal: 1h 19m 33s\tremaining: 7h 45m 20s\n",
            "146:\tlearn: 1.1123514\ttotal: 1h 20m 11s\tremaining: 7h 45m 18s\n",
            "147:\tlearn: 1.1122686\ttotal: 1h 20m 48s\tremaining: 7h 45m 9s\n",
            "148:\tlearn: 1.1119277\ttotal: 1h 21m 25s\tremaining: 7h 45m 4s\n",
            "149:\tlearn: 1.1118752\ttotal: 1h 22m 2s\tremaining: 7h 44m 51s\n",
            "150:\tlearn: 1.1117457\ttotal: 1h 22m 37s\tremaining: 7h 44m 30s\n",
            "151:\tlearn: 1.1116518\ttotal: 1h 23m 8s\tremaining: 7h 43m 52s\n",
            "152:\tlearn: 1.1112471\ttotal: 1h 23m 47s\tremaining: 7h 43m 49s\n",
            "153:\tlearn: 1.1110599\ttotal: 1h 24m 26s\tremaining: 7h 43m 50s\n",
            "154:\tlearn: 1.1109509\ttotal: 1h 25m 1s\tremaining: 7h 43m 29s\n",
            "155:\tlearn: 1.1105355\ttotal: 1h 25m 40s\tremaining: 7h 43m 30s\n",
            "156:\tlearn: 1.1103761\ttotal: 1h 26m 15s\tremaining: 7h 43m 7s\n",
            "158:\tlearn: 1.1100628\ttotal: 1h 27m 17s\tremaining: 7h 41m 43s\n",
            "159:\tlearn: 1.1099732\ttotal: 1h 27m 53s\tremaining: 7h 41m 25s\n",
            "160:\tlearn: 1.1095764\ttotal: 1h 28m 30s\tremaining: 7h 41m 16s\n",
            "161:\tlearn: 1.1094447\ttotal: 1h 28m 57s\tremaining: 7h 40m 8s\n",
            "162:\tlearn: 1.1093351\ttotal: 1h 29m 38s\tremaining: 7h 40m 15s\n",
            "163:\tlearn: 1.1091012\ttotal: 1h 30m 19s\tremaining: 7h 40m 24s\n",
            "164:\tlearn: 1.1090352\ttotal: 1h 30m 52s\tremaining: 7h 39m 52s\n",
            "165:\tlearn: 1.1088543\ttotal: 1h 31m 34s\tremaining: 7h 40m 3s\n",
            "166:\tlearn: 1.1087652\ttotal: 1h 32m 4s\tremaining: 7h 39m 14s\n",
            "167:\tlearn: 1.1086411\ttotal: 1h 32m 34s\tremaining: 7h 38m 25s\n",
            "168:\tlearn: 1.1084730\ttotal: 1h 33m 4s\tremaining: 7h 37m 39s\n",
            "169:\tlearn: 1.1083338\ttotal: 1h 33m 32s\tremaining: 7h 36m 44s\n",
            "170:\tlearn: 1.1082490\ttotal: 1h 34m 4s\tremaining: 7h 36m 5s\n",
            "171:\tlearn: 1.1081219\ttotal: 1h 34m 36s\tremaining: 7h 35m 24s\n",
            "172:\tlearn: 1.1079870\ttotal: 1h 35m 15s\tremaining: 7h 35m 21s\n",
            "173:\tlearn: 1.1078980\ttotal: 1h 35m 51s\tremaining: 7h 35m 1s\n",
            "174:\tlearn: 1.1076555\ttotal: 1h 36m 30s\tremaining: 7h 34m 57s\n",
            "175:\tlearn: 1.1075605\ttotal: 1h 36m 57s\tremaining: 7h 33m 58s\n",
            "176:\tlearn: 1.1074848\ttotal: 1h 37m 38s\tremaining: 7h 34m\n",
            "177:\tlearn: 1.1073901\ttotal: 1h 38m 13s\tremaining: 7h 33m 38s\n",
            "178:\tlearn: 1.1071717\ttotal: 1h 38m 51s\tremaining: 7h 33m 26s\n",
            "179:\tlearn: 1.1071062\ttotal: 1h 39m 25s\tremaining: 7h 32m 53s\n",
            "180:\tlearn: 1.1069687\ttotal: 1h 39m 53s\tremaining: 7h 31m 59s\n",
            "181:\tlearn: 1.1068442\ttotal: 1h 40m 32s\tremaining: 7h 31m 54s\n",
            "182:\tlearn: 1.1067416\ttotal: 1h 41m 6s\tremaining: 7h 31m 24s\n",
            "183:\tlearn: 1.1062449\ttotal: 1h 41m 45s\tremaining: 7h 31m 15s\n",
            "184:\tlearn: 1.1061546\ttotal: 1h 42m 17s\tremaining: 7h 30m 37s\n",
            "185:\tlearn: 1.1060451\ttotal: 1h 42m 48s\tremaining: 7h 29m 55s\n",
            "186:\tlearn: 1.1058983\ttotal: 1h 43m 23s\tremaining: 7h 29m 30s\n",
            "187:\tlearn: 1.1058478\ttotal: 1h 43m 53s\tremaining: 7h 28m 44s\n",
            "188:\tlearn: 1.1057923\ttotal: 1h 44m 23s\tremaining: 7h 27m 55s\n",
            "189:\tlearn: 1.1056706\ttotal: 1h 44m 56s\tremaining: 7h 27m 24s\n",
            "190:\tlearn: 1.1054173\ttotal: 1h 45m 36s\tremaining: 7h 27m 20s\n",
            "191:\tlearn: 1.1053314\ttotal: 1h 46m 14s\tremaining: 7h 27m 4s\n",
            "192:\tlearn: 1.1052272\ttotal: 1h 46m 52s\tremaining: 7h 26m 51s\n",
            "193:\tlearn: 1.1051038\ttotal: 1h 47m 23s\tremaining: 7h 26m 9s\n",
            "194:\tlearn: 1.1050111\ttotal: 1h 47m 53s\tremaining: 7h 25m 24s\n",
            "195:\tlearn: 1.1048665\ttotal: 1h 48m 34s\tremaining: 7h 25m 24s\n",
            "196:\tlearn: 1.1046325\ttotal: 1h 49m 10s\tremaining: 7h 24m 59s\n",
            "197:\tlearn: 1.1043246\ttotal: 1h 49m 48s\tremaining: 7h 24m 47s\n",
            "198:\tlearn: 1.1041888\ttotal: 1h 50m 18s\tremaining: 7h 24m 1s\n",
            "199:\tlearn: 1.1041020\ttotal: 1h 50m 47s\tremaining: 7h 23m 8s\n",
            "200:\tlearn: 1.1040475\ttotal: 1h 51m 24s\tremaining: 7h 22m 53s\n",
            "201:\tlearn: 1.1039390\ttotal: 1h 51m 58s\tremaining: 7h 22m 22s\n",
            "202:\tlearn: 1.1038675\ttotal: 1h 52m 36s\tremaining: 7h 22m 8s\n",
            "203:\tlearn: 1.1038401\ttotal: 1h 53m 10s\tremaining: 7h 21m 34s\n",
            "204:\tlearn: 1.1037523\ttotal: 1h 53m 48s\tremaining: 7h 21m 19s\n",
            "205:\tlearn: 1.1034776\ttotal: 1h 54m 23s\tremaining: 7h 20m 52s\n",
            "206:\tlearn: 1.1033774\ttotal: 1h 54m 55s\tremaining: 7h 20m 16s\n",
            "207:\tlearn: 1.1032245\ttotal: 1h 55m 35s\tremaining: 7h 20m 8s\n",
            "208:\tlearn: 1.1031480\ttotal: 1h 56m 4s\tremaining: 7h 19m 20s\n",
            "209:\tlearn: 1.1030439\ttotal: 1h 56m 45s\tremaining: 7h 19m 15s\n",
            "210:\tlearn: 1.1029765\ttotal: 1h 57m 16s\tremaining: 7h 18m 33s\n",
            "211:\tlearn: 1.1028734\ttotal: 1h 57m 50s\tremaining: 7h 18m\n",
            "212:\tlearn: 1.1028109\ttotal: 1h 58m 33s\tremaining: 7h 18m 4s\n",
            "213:\tlearn: 1.1026816\ttotal: 1h 59m 12s\tremaining: 7h 17m 50s\n",
            "214:\tlearn: 1.1025268\ttotal: 1h 59m 45s\tremaining: 7h 17m 16s\n",
            "215:\tlearn: 1.1024422\ttotal: 2h 23s\tremaining: 7h 17m\n",
            "216:\tlearn: 1.1023152\ttotal: 2h 59s\tremaining: 7h 16m 33s\n",
            "217:\tlearn: 1.1022215\ttotal: 2h 1m 32s\tremaining: 7h 15m 59s\n",
            "218:\tlearn: 1.1018376\ttotal: 2h 2m 9s\tremaining: 7h 15m 40s\n",
            "219:\tlearn: 1.1018080\ttotal: 2h 2m 39s\tremaining: 7h 14m 52s\n",
            "220:\tlearn: 1.1016181\ttotal: 2h 3m 18s\tremaining: 7h 14m 38s\n",
            "221:\tlearn: 1.1015017\ttotal: 2h 3m 55s\tremaining: 7h 14m 19s\n",
            "222:\tlearn: 1.1012647\ttotal: 2h 4m 36s\tremaining: 7h 14m 9s\n",
            "223:\tlearn: 1.1011276\ttotal: 2h 5m 13s\tremaining: 7h 13m 49s\n",
            "224:\tlearn: 1.1010637\ttotal: 2h 5m 54s\tremaining: 7h 13m 41s\n",
            "225:\tlearn: 1.1008488\ttotal: 2h 6m 34s\tremaining: 7h 13m 29s\n",
            "226:\tlearn: 1.1007690\ttotal: 2h 7m 9s\tremaining: 7h 12m 59s\n",
            "227:\tlearn: 1.1007118\ttotal: 2h 7m 37s\tremaining: 7h 12m 6s\n",
            "228:\tlearn: 1.1006401\ttotal: 2h 8m 15s\tremaining: 7h 11m 50s\n",
            "229:\tlearn: 1.1004561\ttotal: 2h 8m 54s\tremaining: 7h 11m 32s\n",
            "230:\tlearn: 1.1003690\ttotal: 2h 9m 31s\tremaining: 7h 11m 11s\n",
            "231:\tlearn: 1.1003019\ttotal: 2h 10m 11s\tremaining: 7h 10m 58s\n",
            "232:\tlearn: 1.1002001\ttotal: 2h 10m 40s\tremaining: 7h 10m 10s\n",
            "233:\tlearn: 1.1000885\ttotal: 2h 11m 14s\tremaining: 7h 9m 35s\n",
            "234:\tlearn: 1.0999202\ttotal: 2h 11m 54s\tremaining: 7h 9m 24s\n",
            "235:\tlearn: 1.0997832\ttotal: 2h 12m 25s\tremaining: 7h 8m 40s\n",
            "236:\tlearn: 1.0997205\ttotal: 2h 13m 6s\tremaining: 7h 8m 33s\n",
            "237:\tlearn: 1.0996350\ttotal: 2h 13m 36s\tremaining: 7h 7m 46s\n",
            "238:\tlearn: 1.0995489\ttotal: 2h 14m 14s\tremaining: 7h 7m 25s\n",
            "239:\tlearn: 1.0994077\ttotal: 2h 14m 47s\tremaining: 7h 6m 49s\n",
            "240:\tlearn: 1.0991989\ttotal: 2h 15m 25s\tremaining: 7h 6m 29s\n",
            "241:\tlearn: 1.0990936\ttotal: 2h 15m 54s\tremaining: 7h 5m 43s\n",
            "242:\tlearn: 1.0989483\ttotal: 2h 16m 25s\tremaining: 7h 5m\n",
            "243:\tlearn: 1.0988505\ttotal: 2h 17m 6s\tremaining: 7h 4m 49s\n",
            "244:\tlearn: 1.0985858\ttotal: 2h 17m 47s\tremaining: 7h 4m 37s\n",
            "245:\tlearn: 1.0984284\ttotal: 2h 18m 27s\tremaining: 7h 4m 22s\n",
            "246:\tlearn: 1.0983575\ttotal: 2h 18m 56s\tremaining: 7h 3m 35s\n",
            "247:\tlearn: 1.0982318\ttotal: 2h 19m 34s\tremaining: 7h 3m 14s\n",
            "248:\tlearn: 1.0981534\ttotal: 2h 20m 7s\tremaining: 7h 2m 37s\n",
            "249:\tlearn: 1.0980598\ttotal: 2h 20m 47s\tremaining: 7h 2m 23s\n",
            "250:\tlearn: 1.0979704\ttotal: 2h 21m 25s\tremaining: 7h 2m\n",
            "251:\tlearn: 1.0978740\ttotal: 2h 21m 55s\tremaining: 7h 1m 14s\n",
            "252:\tlearn: 1.0977976\ttotal: 2h 22m 30s\tremaining: 7h 44s\n",
            "253:\tlearn: 1.0977322\ttotal: 2h 23m 8s\tremaining: 7h 23s\n",
            "254:\tlearn: 1.0976656\ttotal: 2h 23m 46s\tremaining: 7h 3s\n",
            "255:\tlearn: 1.0975807\ttotal: 2h 24m 26s\tremaining: 6h 59m 46s\n",
            "256:\tlearn: 1.0975343\ttotal: 2h 24m 58s\tremaining: 6h 59m 6s\n",
            "257:\tlearn: 1.0974882\ttotal: 2h 25m 24s\tremaining: 6h 58m 10s\n",
            "258:\tlearn: 1.0973930\ttotal: 2h 26m 5s\tremaining: 6h 57m 56s\n",
            "259:\tlearn: 1.0972443\ttotal: 2h 26m 45s\tremaining: 6h 57m 41s\n",
            "260:\tlearn: 1.0971451\ttotal: 2h 27m 24s\tremaining: 6h 57m 22s\n",
            "261:\tlearn: 1.0970823\ttotal: 2h 27m 54s\tremaining: 6h 56m 38s\n",
            "262:\tlearn: 1.0968647\ttotal: 2h 28m 37s\tremaining: 6h 56m 29s\n",
            "263:\tlearn: 1.0967650\ttotal: 2h 29m 10s\tremaining: 6h 55m 53s\n",
            "264:\tlearn: 1.0965941\ttotal: 2h 29m 47s\tremaining: 6h 55m 27s\n",
            "265:\tlearn: 1.0965119\ttotal: 2h 30m 18s\tremaining: 6h 54m 46s\n",
            "266:\tlearn: 1.0964538\ttotal: 2h 30m 54s\tremaining: 6h 54m 16s\n",
            "267:\tlearn: 1.0963745\ttotal: 2h 31m 28s\tremaining: 6h 53m 44s\n",
            "268:\tlearn: 1.0962877\ttotal: 2h 31m 59s\tremaining: 6h 53m 2s\n",
            "269:\tlearn: 1.0962205\ttotal: 2h 32m 40s\tremaining: 6h 52m 47s\n",
            "270:\tlearn: 1.0961324\ttotal: 2h 33m 17s\tremaining: 6h 52m 22s\n",
            "271:\tlearn: 1.0960538\ttotal: 2h 33m 58s\tremaining: 6h 52m 6s\n",
            "272:\tlearn: 1.0959457\ttotal: 2h 34m 37s\tremaining: 6h 51m 44s\n",
            "273:\tlearn: 1.0958798\ttotal: 2h 35m 13s\tremaining: 6h 51m 16s\n",
            "274:\tlearn: 1.0957466\ttotal: 2h 35m 53s\tremaining: 6h 50m 58s\n",
            "275:\tlearn: 1.0956872\ttotal: 2h 36m 28s\tremaining: 6h 50m 27s\n",
            "276:\tlearn: 1.0956345\ttotal: 2h 37m 8s\tremaining: 6h 50m 8s\n",
            "277:\tlearn: 1.0956035\ttotal: 2h 37m 40s\tremaining: 6h 49m 30s\n",
            "278:\tlearn: 1.0955523\ttotal: 2h 38m 9s\tremaining: 6h 48m 42s\n",
            "279:\tlearn: 1.0954881\ttotal: 2h 38m 42s\tremaining: 6h 48m 7s\n",
            "280:\tlearn: 1.0954178\ttotal: 2h 39m 14s\tremaining: 6h 47m 27s\n",
            "281:\tlearn: 1.0953498\ttotal: 2h 39m 56s\tremaining: 6h 47m 13s\n",
            "282:\tlearn: 1.0952671\ttotal: 2h 40m 32s\tremaining: 6h 46m 44s\n",
            "283:\tlearn: 1.0952002\ttotal: 2h 41m 9s\tremaining: 6h 46m 19s\n",
            "284:\tlearn: 1.0951032\ttotal: 2h 41m 49s\tremaining: 6h 45m 58s\n",
            "285:\tlearn: 1.0950675\ttotal: 2h 42m 29s\tremaining: 6h 45m 38s\n",
            "286:\tlearn: 1.0950293\ttotal: 2h 43m 2s\tremaining: 6h 45m 2s\n",
            "287:\tlearn: 1.0949014\ttotal: 2h 43m 40s\tremaining: 6h 44m 38s\n",
            "288:\tlearn: 1.0948464\ttotal: 2h 44m 14s\tremaining: 6h 44m 3s\n",
            "289:\tlearn: 1.0947144\ttotal: 2h 44m 53s\tremaining: 6h 43m 41s\n",
            "290:\tlearn: 1.0946841\ttotal: 2h 45m 27s\tremaining: 6h 43m 8s\n",
            "291:\tlearn: 1.0945535\ttotal: 2h 46m 5s\tremaining: 6h 42m 43s\n",
            "292:\tlearn: 1.0944628\ttotal: 2h 46m 33s\tremaining: 6h 41m 53s\n",
            "293:\tlearn: 1.0944145\ttotal: 2h 47m 14s\tremaining: 6h 41m 37s\n",
            "294:\tlearn: 1.0942855\ttotal: 2h 47m 53s\tremaining: 6h 41m 13s\n",
            "295:\tlearn: 1.0942035\ttotal: 2h 48m 36s\tremaining: 6h 41m\n",
            "296:\tlearn: 1.0940672\ttotal: 2h 49m 16s\tremaining: 6h 40m 39s\n",
            "297:\tlearn: 1.0937420\ttotal: 2h 49m 55s\tremaining: 6h 40m 18s\n",
            "298:\tlearn: 1.0936542\ttotal: 2h 50m 33s\tremaining: 6h 39m 51s\n",
            "299:\tlearn: 1.0935682\ttotal: 2h 51m 6s\tremaining: 6h 39m 15s\n",
            "300:\tlearn: 1.0935061\ttotal: 2h 51m 47s\tremaining: 6h 38m 55s\n",
            "301:\tlearn: 1.0934416\ttotal: 2h 52m 22s\tremaining: 6h 38m 23s\n",
            "302:\tlearn: 1.0933374\ttotal: 2h 52m 54s\tremaining: 6h 37m 45s\n",
            "303:\tlearn: 1.0932042\ttotal: 2h 53m 35s\tremaining: 6h 37m 26s\n",
            "304:\tlearn: 1.0931387\ttotal: 2h 54m 12s\tremaining: 6h 36m 57s\n",
            "305:\tlearn: 1.0930811\ttotal: 2h 54m 42s\tremaining: 6h 36m 14s\n",
            "306:\tlearn: 1.0930245\ttotal: 2h 55m 14s\tremaining: 6h 35m 35s\n",
            "307:\tlearn: 1.0929736\ttotal: 2h 55m 54s\tremaining: 6h 35m 14s\n",
            "308:\tlearn: 1.0929405\ttotal: 2h 56m 29s\tremaining: 6h 34m 41s\n",
            "309:\tlearn: 1.0928625\ttotal: 2h 57m 3s\tremaining: 6h 34m 6s\n",
            "310:\tlearn: 1.0928313\ttotal: 2h 57m 32s\tremaining: 6h 33m 20s\n",
            "311:\tlearn: 1.0926103\ttotal: 2h 58m 11s\tremaining: 6h 32m 55s\n",
            "312:\tlearn: 1.0925400\ttotal: 2h 58m 43s\tremaining: 6h 32m 17s\n",
            "313:\tlearn: 1.0923816\ttotal: 2h 59m 26s\tremaining: 6h 32m 2s\n",
            "314:\tlearn: 1.0921773\ttotal: 3h 4s\tremaining: 6h 31m 34s\n",
            "315:\tlearn: 1.0921250\ttotal: 3h 34s\tremaining: 6h 30m 52s\n",
            "316:\tlearn: 1.0920764\ttotal: 3h 1m 14s\tremaining: 6h 30m 30s\n",
            "317:\tlearn: 1.0920195\ttotal: 3h 1m 54s\tremaining: 6h 30m 7s\n",
            "318:\tlearn: 1.0919505\ttotal: 3h 2m 24s\tremaining: 6h 29m 23s\n",
            "319:\tlearn: 1.0919202\ttotal: 3h 2m 59s\tremaining: 6h 28m 51s\n",
            "320:\tlearn: 1.0918701\ttotal: 3h 3m 32s\tremaining: 6h 28m 14s\n",
            "321:\tlearn: 1.0917957\ttotal: 3h 4m 2s\tremaining: 6h 27m 30s\n",
            "322:\tlearn: 1.0917598\ttotal: 3h 4m 37s\tremaining: 6h 26m 58s\n",
            "323:\tlearn: 1.0916731\ttotal: 3h 5m 5s\tremaining: 6h 26m 11s\n",
            "324:\tlearn: 1.0914375\ttotal: 3h 5m 44s\tremaining: 6h 25m 45s\n",
            "325:\tlearn: 1.0913750\ttotal: 3h 6m 14s\tremaining: 6h 25m 3s\n",
            "326:\tlearn: 1.0912708\ttotal: 3h 6m 41s\tremaining: 6h 24m 13s\n",
            "327:\tlearn: 1.0912101\ttotal: 3h 7m 19s\tremaining: 6h 23m 47s\n",
            "328:\tlearn: 1.0911601\ttotal: 3h 7m 50s\tremaining: 6h 23m 6s\n",
            "329:\tlearn: 1.0911180\ttotal: 3h 8m 29s\tremaining: 6h 22m 41s\n",
            "330:\tlearn: 1.0910550\ttotal: 3h 8m 59s\tremaining: 6h 21m 59s\n",
            "331:\tlearn: 1.0910160\ttotal: 3h 9m 44s\tremaining: 6h 21m 45s\n",
            "332:\tlearn: 1.0909566\ttotal: 3h 10m 21s\tremaining: 6h 21m 17s\n",
            "333:\tlearn: 1.0909291\ttotal: 3h 10m 52s\tremaining: 6h 20m 37s\n",
            "334:\tlearn: 1.0908122\ttotal: 3h 11m 28s\tremaining: 6h 20m 5s\n",
            "335:\tlearn: 1.0907648\ttotal: 3h 12m 6s\tremaining: 6h 19m 38s\n",
            "336:\tlearn: 1.0907447\ttotal: 3h 12m 35s\tremaining: 6h 18m 53s\n",
            "337:\tlearn: 1.0906754\ttotal: 3h 13m 14s\tremaining: 6h 18m 29s\n",
            "338:\tlearn: 1.0905356\ttotal: 3h 13m 51s\tremaining: 6h 17m 59s\n",
            "339:\tlearn: 1.0904238\ttotal: 3h 14m 32s\tremaining: 6h 17m 38s\n",
            "340:\tlearn: 1.0903768\ttotal: 3h 15m 4s\tremaining: 6h 16m 59s\n",
            "341:\tlearn: 1.0903199\ttotal: 3h 15m 33s\tremaining: 6h 16m 14s\n",
            "342:\tlearn: 1.0902730\ttotal: 3h 16m 3s\tremaining: 6h 15m 33s\n",
            "343:\tlearn: 1.0900475\ttotal: 3h 16m 45s\tremaining: 6h 15m 12s\n",
            "344:\tlearn: 1.0899909\ttotal: 3h 17m 16s\tremaining: 6h 14m 32s\n",
            "345:\tlearn: 1.0896998\ttotal: 3h 17m 57s\tremaining: 6h 14m 10s\n",
            "346:\tlearn: 1.0896396\ttotal: 3h 18m 25s\tremaining: 6h 13m 23s\n",
            "347:\tlearn: 1.0894571\ttotal: 3h 19m 4s\tremaining: 6h 12m 58s\n",
            "348:\tlearn: 1.0893962\ttotal: 3h 19m 37s\tremaining: 6h 12m 22s\n",
            "349:\tlearn: 1.0892583\ttotal: 3h 20m 12s\tremaining: 6h 11m 49s\n",
            "350:\tlearn: 1.0892087\ttotal: 3h 20m 39s\tremaining: 6h 11m\n",
            "351:\tlearn: 1.0891619\ttotal: 3h 21m 11s\tremaining: 6h 10m 22s\n",
            "352:\tlearn: 1.0890851\ttotal: 3h 21m 44s\tremaining: 6h 9m 46s\n",
            "353:\tlearn: 1.0890548\ttotal: 3h 22m 15s\tremaining: 6h 9m 5s\n",
            "354:\tlearn: 1.0890137\ttotal: 3h 22m 51s\tremaining: 6h 8m 34s\n",
            "355:\tlearn: 1.0889113\ttotal: 3h 23m 31s\tremaining: 6h 8m 9s\n",
            "356:\tlearn: 1.0888964\ttotal: 3h 24m 6s\tremaining: 6h 7m 37s\n",
            "357:\tlearn: 1.0886239\ttotal: 3h 24m 48s\tremaining: 6h 7m 16s\n",
            "358:\tlearn: 1.0885628\ttotal: 3h 25m 27s\tremaining: 6h 6m 50s\n",
            "359:\tlearn: 1.0885082\ttotal: 3h 25m 52s\tremaining: 6h 6m\n",
            "360:\tlearn: 1.0884817\ttotal: 3h 26m 35s\tremaining: 6h 5m 40s\n",
            "361:\tlearn: 1.0884304\ttotal: 3h 27m 14s\tremaining: 6h 5m 15s\n",
            "362:\tlearn: 1.0883226\ttotal: 3h 27m 56s\tremaining: 6h 4m 54s\n",
            "363:\tlearn: 1.0882672\ttotal: 3h 28m 28s\tremaining: 6h 4m 16s\n",
            "364:\tlearn: 1.0882211\ttotal: 3h 29m 9s\tremaining: 6h 3m 52s\n",
            "365:\tlearn: 1.0881697\ttotal: 3h 29m 41s\tremaining: 6h 3m 13s\n",
            "366:\tlearn: 1.0880927\ttotal: 3h 30m 19s\tremaining: 6h 2m 45s\n",
            "367:\tlearn: 1.0880342\ttotal: 3h 30m 55s\tremaining: 6h 2m 13s\n",
            "368:\tlearn: 1.0879812\ttotal: 3h 31m 29s\tremaining: 6h 1m 38s\n",
            "369:\tlearn: 1.0879045\ttotal: 3h 31m 55s\tremaining: 6h 50s\n",
            "370:\tlearn: 1.0878795\ttotal: 3h 32m 28s\tremaining: 6h 14s\n",
            "371:\tlearn: 1.0878431\ttotal: 3h 32m 56s\tremaining: 5h 59m 29s\n",
            "372:\tlearn: 1.0877868\ttotal: 3h 33m 30s\tremaining: 5h 58m 53s\n",
            "373:\tlearn: 1.0877128\ttotal: 3h 34m 9s\tremaining: 5h 58m 28s\n",
            "374:\tlearn: 1.0875937\ttotal: 3h 34m 45s\tremaining: 5h 57m 56s\n",
            "375:\tlearn: 1.0874312\ttotal: 3h 35m 26s\tremaining: 5h 57m 32s\n",
            "376:\tlearn: 1.0873998\ttotal: 3h 35m 56s\tremaining: 5h 56m 51s\n",
            "377:\tlearn: 1.0873512\ttotal: 3h 36m 26s\tremaining: 5h 56m 9s\n",
            "378:\tlearn: 1.0872831\ttotal: 3h 37m\tremaining: 5h 55m 34s\n",
            "379:\tlearn: 1.0872470\ttotal: 3h 37m 36s\tremaining: 5h 55m 1s\n",
            "380:\tlearn: 1.0872068\ttotal: 3h 38m 7s\tremaining: 5h 54m 22s\n",
            "381:\tlearn: 1.0871598\ttotal: 3h 38m 43s\tremaining: 5h 53m 50s\n",
            "382:\tlearn: 1.0870489\ttotal: 3h 39m 18s\tremaining: 5h 53m 18s\n",
            "383:\tlearn: 1.0870038\ttotal: 3h 39m 50s\tremaining: 5h 52m 39s\n",
            "384:\tlearn: 1.0869447\ttotal: 3h 40m 23s\tremaining: 5h 52m 3s\n",
            "385:\tlearn: 1.0866932\ttotal: 3h 41m 4s\tremaining: 5h 51m 40s\n",
            "386:\tlearn: 1.0866303\ttotal: 3h 41m 46s\tremaining: 5h 51m 16s\n",
            "387:\tlearn: 1.0865235\ttotal: 3h 42m 23s\tremaining: 5h 50m 47s\n",
            "388:\tlearn: 1.0864425\ttotal: 3h 42m 56s\tremaining: 5h 50m 11s\n",
            "389:\tlearn: 1.0863823\ttotal: 3h 43m 33s\tremaining: 5h 49m 40s\n",
            "390:\tlearn: 1.0863072\ttotal: 3h 44m 9s\tremaining: 5h 49m 8s\n",
            "391:\tlearn: 1.0862513\ttotal: 3h 44m 44s\tremaining: 5h 48m 34s\n",
            "392:\tlearn: 1.0862056\ttotal: 3h 45m 14s\tremaining: 5h 47m 52s\n",
            "393:\tlearn: 1.0861866\ttotal: 3h 45m 45s\tremaining: 5h 47m 14s\n",
            "394:\tlearn: 1.0861688\ttotal: 3h 46m 24s\tremaining: 5h 46m 46s\n",
            "395:\tlearn: 1.0860440\ttotal: 3h 47m 5s\tremaining: 5h 46m 22s\n",
            "396:\tlearn: 1.0859948\ttotal: 3h 47m 34s\tremaining: 5h 45m 39s\n",
            "397:\tlearn: 1.0859231\ttotal: 3h 48m 15s\tremaining: 5h 45m 16s\n",
            "398:\tlearn: 1.0858256\ttotal: 3h 48m 53s\tremaining: 5h 44m 46s\n",
            "399:\tlearn: 1.0857139\ttotal: 3h 49m 34s\tremaining: 5h 44m 21s\n",
            "400:\tlearn: 1.0856427\ttotal: 3h 50m 14s\tremaining: 5h 43m 55s\n",
            "401:\tlearn: 1.0855382\ttotal: 3h 50m 54s\tremaining: 5h 43m 29s\n",
            "402:\tlearn: 1.0854871\ttotal: 3h 51m 23s\tremaining: 5h 42m 47s\n",
            "403:\tlearn: 1.0853909\ttotal: 3h 52m 5s\tremaining: 5h 42m 23s\n",
            "404:\tlearn: 1.0853432\ttotal: 3h 52m 38s\tremaining: 5h 41m 47s\n",
            "405:\tlearn: 1.0853222\ttotal: 3h 53m 3s\tremaining: 5h 40m 58s\n",
            "406:\tlearn: 1.0852337\ttotal: 3h 53m 44s\tremaining: 5h 40m 34s\n",
            "407:\tlearn: 1.0851905\ttotal: 3h 54m 22s\tremaining: 5h 40m 3s\n",
            "408:\tlearn: 1.0851565\ttotal: 3h 54m 52s\tremaining: 5h 39m 23s\n",
            "409:\tlearn: 1.0850906\ttotal: 3h 55m 27s\tremaining: 5h 38m 50s\n",
            "410:\tlearn: 1.0850043\ttotal: 3h 56m 8s\tremaining: 5h 38m 25s\n",
            "411:\tlearn: 1.0849631\ttotal: 3h 56m 43s\tremaining: 5h 37m 51s\n",
            "412:\tlearn: 1.0849375\ttotal: 3h 57m 18s\tremaining: 5h 37m 17s\n",
            "413:\tlearn: 1.0848964\ttotal: 3h 57m 47s\tremaining: 5h 36m 34s\n",
            "414:\tlearn: 1.0848642\ttotal: 3h 58m 20s\tremaining: 5h 35m 58s\n",
            "415:\tlearn: 1.0848107\ttotal: 3h 58m 54s\tremaining: 5h 35m 22s\n",
            "416:\tlearn: 1.0847635\ttotal: 3h 59m 29s\tremaining: 5h 34m 50s\n",
            "417:\tlearn: 1.0847252\ttotal: 4h 3s\tremaining: 5h 34m 14s\n",
            "418:\tlearn: 1.0846955\ttotal: 4h 46s\tremaining: 5h 33m 52s\n",
            "419:\tlearn: 1.0846801\ttotal: 4h 1m 26s\tremaining: 5h 33m 25s\n",
            "420:\tlearn: 1.0845319\ttotal: 4h 2m 1s\tremaining: 5h 32m 51s\n",
            "421:\tlearn: 1.0845106\ttotal: 4h 2m 33s\tremaining: 5h 32m 13s\n",
            "422:\tlearn: 1.0844714\ttotal: 4h 3m 7s\tremaining: 5h 31m 38s\n",
            "423:\tlearn: 1.0844439\ttotal: 4h 3m 37s\tremaining: 5h 30m 57s\n",
            "424:\tlearn: 1.0844071\ttotal: 4h 4m 5s\tremaining: 5h 30m 14s\n",
            "425:\tlearn: 1.0843418\ttotal: 4h 4m 37s\tremaining: 5h 29m 37s\n",
            "426:\tlearn: 1.0842331\ttotal: 4h 5m 12s\tremaining: 5h 29m 3s\n",
            "427:\tlearn: 1.0841041\ttotal: 4h 5m 51s\tremaining: 5h 28m 34s\n",
            "428:\tlearn: 1.0840705\ttotal: 4h 6m 23s\tremaining: 5h 27m 56s\n",
            "429:\tlearn: 1.0840511\ttotal: 4h 6m 49s\tremaining: 5h 27m 11s\n",
            "430:\tlearn: 1.0840124\ttotal: 4h 7m 28s\tremaining: 5h 26m 42s\n",
            "431:\tlearn: 1.0839778\ttotal: 4h 8m 8s\tremaining: 5h 26m 15s\n",
            "432:\tlearn: 1.0839291\ttotal: 4h 8m 45s\tremaining: 5h 25m 44s\n",
            "433:\tlearn: 1.0838802\ttotal: 4h 9m 18s\tremaining: 5h 25m 7s\n",
            "434:\tlearn: 1.0837833\ttotal: 4h 9m 57s\tremaining: 5h 24m 38s\n",
            "435:\tlearn: 1.0837000\ttotal: 4h 10m 39s\tremaining: 5h 24m 14s\n",
            "436:\tlearn: 1.0836614\ttotal: 4h 11m 14s\tremaining: 5h 23m 40s\n",
            "437:\tlearn: 1.0836000\ttotal: 4h 11m 42s\tremaining: 5h 22m 57s\n",
            "438:\tlearn: 1.0835621\ttotal: 4h 12m 21s\tremaining: 5h 22m 29s\n",
            "439:\tlearn: 1.0834686\ttotal: 4h 12m 59s\tremaining: 5h 21m 59s\n",
            "440:\tlearn: 1.0834368\ttotal: 4h 13m 39s\tremaining: 5h 21m 31s\n",
            "441:\tlearn: 1.0833966\ttotal: 4h 14m 20s\tremaining: 5h 21m 5s\n",
            "442:\tlearn: 1.0833421\ttotal: 4h 15m\tremaining: 5h 20m 38s\n",
            "443:\tlearn: 1.0832598\ttotal: 4h 15m 41s\tremaining: 5h 20m 11s\n",
            "444:\tlearn: 1.0832317\ttotal: 4h 16m 12s\tremaining: 5h 19m 32s\n",
            "445:\tlearn: 1.0831759\ttotal: 4h 16m 51s\tremaining: 5h 19m 3s\n",
            "446:\tlearn: 1.0831386\ttotal: 4h 17m 21s\tremaining: 5h 18m 22s\n",
            "447:\tlearn: 1.0830793\ttotal: 4h 17m 56s\tremaining: 5h 17m 49s\n",
            "448:\tlearn: 1.0830061\ttotal: 4h 18m 36s\tremaining: 5h 17m 21s\n",
            "449:\tlearn: 1.0829532\ttotal: 4h 19m 14s\tremaining: 5h 16m 51s\n",
            "450:\tlearn: 1.0828637\ttotal: 4h 19m 55s\tremaining: 5h 16m 24s\n",
            "451:\tlearn: 1.0828048\ttotal: 4h 20m 36s\tremaining: 5h 15m 57s\n",
            "452:\tlearn: 1.0826928\ttotal: 4h 21m 18s\tremaining: 5h 15m 31s\n",
            "453:\tlearn: 1.0826627\ttotal: 4h 21m 54s\tremaining: 5h 14m 58s\n",
            "454:\tlearn: 1.0826164\ttotal: 4h 22m 34s\tremaining: 5h 14m 30s\n",
            "455:\tlearn: 1.0825795\ttotal: 4h 23m 6s\tremaining: 5h 13m 52s\n",
            "456:\tlearn: 1.0825538\ttotal: 4h 23m 44s\tremaining: 5h 13m 21s\n",
            "457:\tlearn: 1.0824561\ttotal: 4h 24m 21s\tremaining: 5h 12m 50s\n",
            "458:\tlearn: 1.0824116\ttotal: 4h 24m 54s\tremaining: 5h 12m 13s\n",
            "459:\tlearn: 1.0823545\ttotal: 4h 25m 29s\tremaining: 5h 11m 39s\n",
            "460:\tlearn: 1.0823271\ttotal: 4h 26m 6s\tremaining: 5h 11m 8s\n",
            "461:\tlearn: 1.0822765\ttotal: 4h 26m 37s\tremaining: 5h 10m 29s\n",
            "462:\tlearn: 1.0822221\ttotal: 4h 27m 15s\tremaining: 5h 9m 58s\n",
            "463:\tlearn: 1.0822021\ttotal: 4h 27m 49s\tremaining: 5h 9m 22s\n",
            "464:\tlearn: 1.0821077\ttotal: 4h 28m 22s\tremaining: 5h 8m 45s\n",
            "465:\tlearn: 1.0820531\ttotal: 4h 28m 58s\tremaining: 5h 8m 13s\n",
            "466:\tlearn: 1.0819984\ttotal: 4h 29m 30s\tremaining: 5h 7m 35s\n",
            "467:\tlearn: 1.0819481\ttotal: 4h 30m 4s\tremaining: 5h 7m\n",
            "468:\tlearn: 1.0819063\ttotal: 4h 30m 45s\tremaining: 5h 6m 33s\n",
            "469:\tlearn: 1.0818043\ttotal: 4h 31m 24s\tremaining: 5h 6m 3s\n",
            "470:\tlearn: 1.0817505\ttotal: 4h 31m 56s\tremaining: 5h 5m 26s\n",
            "471:\tlearn: 1.0817389\ttotal: 4h 32m 33s\tremaining: 5h 4m 53s\n",
            "472:\tlearn: 1.0816900\ttotal: 4h 33m 13s\tremaining: 5h 4m 24s\n",
            "473:\tlearn: 1.0816203\ttotal: 4h 33m 52s\tremaining: 5h 3m 55s\n",
            "474:\tlearn: 1.0815904\ttotal: 4h 34m 21s\tremaining: 5h 3m 14s\n",
            "475:\tlearn: 1.0815659\ttotal: 4h 34m 54s\tremaining: 5h 2m 37s\n",
            "476:\tlearn: 1.0815331\ttotal: 4h 35m 34s\tremaining: 5h 2m 9s\n",
            "477:\tlearn: 1.0814935\ttotal: 4h 36m 8s\tremaining: 5h 1m 33s\n",
            "478:\tlearn: 1.0814549\ttotal: 4h 36m 41s\tremaining: 5h 57s\n",
            "479:\tlearn: 1.0814280\ttotal: 4h 37m 11s\tremaining: 5h 17s\n",
            "480:\tlearn: 1.0813983\ttotal: 4h 37m 47s\tremaining: 4h 59m 44s\n",
            "481:\tlearn: 1.0813568\ttotal: 4h 38m 20s\tremaining: 4h 59m 8s\n",
            "482:\tlearn: 1.0813097\ttotal: 4h 38m 58s\tremaining: 4h 58m 36s\n",
            "483:\tlearn: 1.0812563\ttotal: 4h 39m 29s\tremaining: 4h 57m 57s\n",
            "484:\tlearn: 1.0812085\ttotal: 4h 40m 5s\tremaining: 4h 57m 25s\n",
            "485:\tlearn: 1.0811656\ttotal: 4h 40m 39s\tremaining: 4h 56m 49s\n",
            "486:\tlearn: 1.0811241\ttotal: 4h 41m 16s\tremaining: 4h 56m 17s\n",
            "487:\tlearn: 1.0810711\ttotal: 4h 41m 47s\tremaining: 4h 55m 38s\n",
            "488:\tlearn: 1.0810004\ttotal: 4h 42m 21s\tremaining: 4h 55m 3s\n",
            "489:\tlearn: 1.0809444\ttotal: 4h 42m 55s\tremaining: 4h 54m 28s\n",
            "490:\tlearn: 1.0809046\ttotal: 4h 43m 30s\tremaining: 4h 53m 54s\n",
            "491:\tlearn: 1.0808394\ttotal: 4h 44m 8s\tremaining: 4h 53m 23s\n",
            "492:\tlearn: 1.0808072\ttotal: 4h 44m 45s\tremaining: 4h 52m 51s\n",
            "493:\tlearn: 1.0807685\ttotal: 4h 45m 15s\tremaining: 4h 52m 11s\n",
            "494:\tlearn: 1.0807065\ttotal: 4h 45m 57s\tremaining: 4h 51m 44s\n",
            "495:\tlearn: 1.0806361\ttotal: 4h 46m 34s\tremaining: 4h 51m 11s\n",
            "496:\tlearn: 1.0806107\ttotal: 4h 47m 7s\tremaining: 4h 50m 35s\n",
            "497:\tlearn: 1.0805710\ttotal: 4h 47m 45s\tremaining: 4h 50m 4s\n",
            "498:\tlearn: 1.0805350\ttotal: 4h 48m 18s\tremaining: 4h 49m 27s\n",
            "499:\tlearn: 1.0804833\ttotal: 4h 48m 56s\tremaining: 4h 48m 56s\n",
            "500:\tlearn: 1.0804440\ttotal: 4h 49m 30s\tremaining: 4h 48m 21s\n",
            "501:\tlearn: 1.0804225\ttotal: 4h 50m 1s\tremaining: 4h 47m 42s\n",
            "502:\tlearn: 1.0804037\ttotal: 4h 50m 37s\tremaining: 4h 47m 9s\n",
            "503:\tlearn: 1.0803505\ttotal: 4h 51m 14s\tremaining: 4h 46m 37s\n",
            "504:\tlearn: 1.0803074\ttotal: 4h 51m 45s\tremaining: 4h 45m 59s\n",
            "505:\tlearn: 1.0802741\ttotal: 4h 52m 13s\tremaining: 4h 45m 17s\n",
            "506:\tlearn: 1.0802357\ttotal: 4h 52m 49s\tremaining: 4h 44m 44s\n",
            "507:\tlearn: 1.0802193\ttotal: 4h 53m 30s\tremaining: 4h 44m 16s\n",
            "508:\tlearn: 1.0801592\ttotal: 4h 53m 58s\tremaining: 4h 43m 35s\n",
            "509:\tlearn: 1.0800947\ttotal: 4h 54m 39s\tremaining: 4h 43m 6s\n",
            "510:\tlearn: 1.0800756\ttotal: 4h 55m 14s\tremaining: 4h 42m 31s\n",
            "511:\tlearn: 1.0800405\ttotal: 4h 55m 51s\tremaining: 4h 41m 59s\n",
            "512:\tlearn: 1.0800221\ttotal: 4h 56m 21s\tremaining: 4h 41m 20s\n",
            "513:\tlearn: 1.0799686\ttotal: 4h 56m 54s\tremaining: 4h 40m 43s\n",
            "514:\tlearn: 1.0799166\ttotal: 4h 57m 28s\tremaining: 4h 40m 8s\n",
            "515:\tlearn: 1.0798876\ttotal: 4h 58m 2s\tremaining: 4h 39m 33s\n",
            "516:\tlearn: 1.0798445\ttotal: 4h 58m 32s\tremaining: 4h 38m 54s\n",
            "517:\tlearn: 1.0798044\ttotal: 4h 58m 56s\tremaining: 4h 38m 10s\n",
            "518:\tlearn: 1.0797726\ttotal: 4h 59m 31s\tremaining: 4h 37m 35s\n",
            "519:\tlearn: 1.0797011\ttotal: 5h\tremaining: 4h 36m 56s\n",
            "520:\tlearn: 1.0796313\ttotal: 5h 35s\tremaining: 4h 36m 21s\n",
            "521:\tlearn: 1.0795892\ttotal: 5h 1m 15s\tremaining: 4h 35m 51s\n",
            "522:\tlearn: 1.0795624\ttotal: 5h 1m 46s\tremaining: 4h 35m 14s\n",
            "523:\tlearn: 1.0795505\ttotal: 5h 2m 19s\tremaining: 4h 34m 38s\n",
            "524:\tlearn: 1.0794457\ttotal: 5h 3m\tremaining: 4h 34m 8s\n",
            "525:\tlearn: 1.0794296\ttotal: 5h 3m 26s\tremaining: 4h 33m 26s\n",
            "526:\tlearn: 1.0793702\ttotal: 5h 4m 4s\tremaining: 4h 32m 55s\n",
            "527:\tlearn: 1.0793047\ttotal: 5h 4m 42s\tremaining: 4h 32m 23s\n",
            "528:\tlearn: 1.0792503\ttotal: 5h 5m 16s\tremaining: 4h 31m 47s\n",
            "529:\tlearn: 1.0792343\ttotal: 5h 5m 58s\tremaining: 4h 31m 20s\n",
            "530:\tlearn: 1.0791642\ttotal: 5h 6m 39s\tremaining: 4h 30m 51s\n",
            "531:\tlearn: 1.0791420\ttotal: 5h 7m 10s\tremaining: 4h 30m 13s\n",
            "532:\tlearn: 1.0791145\ttotal: 5h 7m 38s\tremaining: 4h 29m 32s\n",
            "533:\tlearn: 1.0790724\ttotal: 5h 8m 12s\tremaining: 4h 28m 57s\n",
            "534:\tlearn: 1.0790137\ttotal: 5h 8m 45s\tremaining: 4h 28m 21s\n",
            "535:\tlearn: 1.0789943\ttotal: 5h 9m 16s\tremaining: 4h 27m 43s\n",
            "536:\tlearn: 1.0788929\ttotal: 5h 9m 52s\tremaining: 4h 27m 10s\n",
            "537:\tlearn: 1.0788392\ttotal: 5h 10m 31s\tremaining: 4h 26m 39s\n",
            "538:\tlearn: 1.0787968\ttotal: 5h 11m 5s\tremaining: 4h 26m 3s\n",
            "539:\tlearn: 1.0787147\ttotal: 5h 11m 41s\tremaining: 4h 25m 31s\n",
            "540:\tlearn: 1.0786730\ttotal: 5h 12m 11s\tremaining: 4h 24m 52s\n",
            "541:\tlearn: 1.0786373\ttotal: 5h 12m 41s\tremaining: 4h 24m 14s\n",
            "542:\tlearn: 1.0785764\ttotal: 5h 13m 12s\tremaining: 4h 23m 36s\n",
            "543:\tlearn: 1.0785331\ttotal: 5h 13m 51s\tremaining: 4h 23m 5s\n",
            "544:\tlearn: 1.0785051\ttotal: 5h 14m 31s\tremaining: 4h 22m 35s\n",
            "545:\tlearn: 1.0784616\ttotal: 5h 15m 11s\tremaining: 4h 22m 4s\n",
            "546:\tlearn: 1.0783812\ttotal: 5h 15m 49s\tremaining: 4h 21m 32s\n",
            "547:\tlearn: 1.0783300\ttotal: 5h 16m 22s\tremaining: 4h 20m 57s\n",
            "548:\tlearn: 1.0783091\ttotal: 5h 16m 52s\tremaining: 4h 20m 18s\n",
            "549:\tlearn: 1.0782827\ttotal: 5h 17m 30s\tremaining: 4h 19m 46s\n",
            "550:\tlearn: 1.0782307\ttotal: 5h 18m 11s\tremaining: 4h 19m 17s\n",
            "551:\tlearn: 1.0781805\ttotal: 5h 18m 40s\tremaining: 4h 18m 38s\n",
            "552:\tlearn: 1.0781645\ttotal: 5h 19m 10s\tremaining: 4h 17m 59s\n",
            "553:\tlearn: 1.0781296\ttotal: 5h 19m 45s\tremaining: 4h 17m 25s\n",
            "554:\tlearn: 1.0780969\ttotal: 5h 20m 18s\tremaining: 4h 16m 49s\n",
            "555:\tlearn: 1.0780418\ttotal: 5h 20m 55s\tremaining: 4h 16m 17s\n",
            "556:\tlearn: 1.0780113\ttotal: 5h 21m 38s\tremaining: 4h 15m 48s\n",
            "557:\tlearn: 1.0779675\ttotal: 5h 22m 10s\tremaining: 4h 15m 11s\n",
            "558:\tlearn: 1.0779512\ttotal: 5h 22m 49s\tremaining: 4h 14m 40s\n",
            "559:\tlearn: 1.0779057\ttotal: 5h 23m 26s\tremaining: 4h 14m 8s\n",
            "560:\tlearn: 1.0778927\ttotal: 5h 23m 56s\tremaining: 4h 13m 29s\n",
            "561:\tlearn: 1.0778546\ttotal: 5h 24m 37s\tremaining: 4h 13m\n",
            "562:\tlearn: 1.0778244\ttotal: 5h 25m 8s\tremaining: 4h 12m 22s\n",
            "563:\tlearn: 1.0777757\ttotal: 5h 25m 44s\tremaining: 4h 11m 48s\n",
            "564:\tlearn: 1.0777474\ttotal: 5h 26m 25s\tremaining: 4h 11m 19s\n",
            "565:\tlearn: 1.0777140\ttotal: 5h 26m 55s\tremaining: 4h 10m 40s\n",
            "566:\tlearn: 1.0776771\ttotal: 5h 27m 24s\tremaining: 4h 10m 2s\n",
            "567:\tlearn: 1.0776304\ttotal: 5h 28m 3s\tremaining: 4h 9m 30s\n",
            "568:\tlearn: 1.0775833\ttotal: 5h 28m 36s\tremaining: 4h 8m 54s\n",
            "569:\tlearn: 1.0775342\ttotal: 5h 29m 13s\tremaining: 4h 8m 21s\n",
            "570:\tlearn: 1.0775119\ttotal: 5h 29m 48s\tremaining: 4h 7m 47s\n",
            "571:\tlearn: 1.0774766\ttotal: 5h 30m 20s\tremaining: 4h 7m 10s\n",
            "572:\tlearn: 1.0773560\ttotal: 5h 31m 1s\tremaining: 4h 6m 40s\n",
            "573:\tlearn: 1.0773044\ttotal: 5h 31m 27s\tremaining: 4h 5m 59s\n",
            "574:\tlearn: 1.0772742\ttotal: 5h 32m 2s\tremaining: 4h 5m 25s\n",
            "575:\tlearn: 1.0772504\ttotal: 5h 32m 31s\tremaining: 4h 4m 46s\n",
            "576:\tlearn: 1.0772162\ttotal: 5h 33m 3s\tremaining: 4h 4m 9s\n",
            "577:\tlearn: 1.0771583\ttotal: 5h 33m 43s\tremaining: 4h 3m 39s\n",
            "578:\tlearn: 1.0771188\ttotal: 5h 34m 19s\tremaining: 4h 3m 5s\n",
            "579:\tlearn: 1.0770997\ttotal: 5h 34m 53s\tremaining: 4h 2m 30s\n",
            "580:\tlearn: 1.0770691\ttotal: 5h 35m 28s\tremaining: 4h 1m 55s\n",
            "581:\tlearn: 1.0770157\ttotal: 5h 35m 57s\tremaining: 4h 1m 17s\n",
            "582:\tlearn: 1.0768993\ttotal: 5h 36m 38s\tremaining: 4h 47s\n",
            "583:\tlearn: 1.0768320\ttotal: 5h 37m 12s\tremaining: 4h 12s\n",
            "584:\tlearn: 1.0767953\ttotal: 5h 37m 43s\tremaining: 3h 59m 34s\n",
            "585:\tlearn: 1.0767526\ttotal: 5h 38m 11s\tremaining: 3h 58m 55s\n",
            "586:\tlearn: 1.0767131\ttotal: 5h 38m 40s\tremaining: 3h 58m 16s\n",
            "587:\tlearn: 1.0766732\ttotal: 5h 39m 15s\tremaining: 3h 57m 42s\n",
            "588:\tlearn: 1.0765796\ttotal: 5h 39m 56s\tremaining: 3h 57m 12s\n",
            "589:\tlearn: 1.0765303\ttotal: 5h 40m 29s\tremaining: 3h 56m 37s\n",
            "590:\tlearn: 1.0765031\ttotal: 5h 40m 55s\tremaining: 3h 55m 56s\n",
            "591:\tlearn: 1.0764689\ttotal: 5h 41m 29s\tremaining: 3h 55m 20s\n",
            "592:\tlearn: 1.0764045\ttotal: 5h 41m 59s\tremaining: 3h 54m 43s\n",
            "593:\tlearn: 1.0763918\ttotal: 5h 42m 32s\tremaining: 3h 54m 7s\n",
            "594:\tlearn: 1.0763216\ttotal: 5h 43m 13s\tremaining: 3h 53m 37s\n",
            "595:\tlearn: 1.0762723\ttotal: 5h 43m 49s\tremaining: 3h 53m 3s\n",
            "596:\tlearn: 1.0762561\ttotal: 5h 44m 19s\tremaining: 3h 52m 26s\n",
            "597:\tlearn: 1.0761076\ttotal: 5h 44m 56s\tremaining: 3h 51m 52s\n",
            "598:\tlearn: 1.0759857\ttotal: 5h 45m 36s\tremaining: 3h 51m 21s\n",
            "599:\tlearn: 1.0759410\ttotal: 5h 46m 8s\tremaining: 3h 50m 45s\n",
            "600:\tlearn: 1.0759029\ttotal: 5h 46m 47s\tremaining: 3h 50m 13s\n",
            "601:\tlearn: 1.0758699\ttotal: 5h 47m 14s\tremaining: 3h 49m 34s\n",
            "602:\tlearn: 1.0757487\ttotal: 5h 47m 49s\tremaining: 3h 49m\n",
            "603:\tlearn: 1.0756863\ttotal: 5h 48m 27s\tremaining: 3h 48m 27s\n",
            "604:\tlearn: 1.0756558\ttotal: 5h 48m 59s\tremaining: 3h 47m 51s\n",
            "605:\tlearn: 1.0756267\ttotal: 5h 49m 30s\tremaining: 3h 47m 14s\n",
            "606:\tlearn: 1.0756125\ttotal: 5h 50m 1s\tremaining: 3h 46m 37s\n",
            "607:\tlearn: 1.0755968\ttotal: 5h 50m 34s\tremaining: 3h 46m 1s\n",
            "608:\tlearn: 1.0755686\ttotal: 5h 51m 7s\tremaining: 3h 45m 25s\n",
            "609:\tlearn: 1.0754987\ttotal: 5h 51m 46s\tremaining: 3h 44m 54s\n",
            "610:\tlearn: 1.0754707\ttotal: 5h 52m 23s\tremaining: 3h 44m 21s\n",
            "611:\tlearn: 1.0754318\ttotal: 5h 52m 56s\tremaining: 3h 43m 45s\n",
            "612:\tlearn: 1.0752767\ttotal: 5h 53m 32s\tremaining: 3h 43m 12s\n",
            "613:\tlearn: 1.0752234\ttotal: 5h 54m 8s\tremaining: 3h 42m 38s\n",
            "614:\tlearn: 1.0751806\ttotal: 5h 54m 50s\tremaining: 3h 42m 8s\n",
            "615:\tlearn: 1.0750881\ttotal: 5h 55m 26s\tremaining: 3h 41m 34s\n",
            "616:\tlearn: 1.0750229\ttotal: 5h 56m 1s\tremaining: 3h 41m\n",
            "617:\tlearn: 1.0749769\ttotal: 5h 56m 35s\tremaining: 3h 40m 24s\n",
            "618:\tlearn: 1.0749447\ttotal: 5h 57m 15s\tremaining: 3h 39m 53s\n",
            "619:\tlearn: 1.0749187\ttotal: 5h 57m 52s\tremaining: 3h 39m 20s\n",
            "620:\tlearn: 1.0748536\ttotal: 5h 58m 32s\tremaining: 3h 38m 49s\n",
            "621:\tlearn: 1.0748226\ttotal: 5h 59m 6s\tremaining: 3h 38m 14s\n",
            "622:\tlearn: 1.0747950\ttotal: 5h 59m 40s\tremaining: 3h 37m 39s\n",
            "623:\tlearn: 1.0747145\ttotal: 6h 17s\tremaining: 3h 37m 6s\n",
            "624:\tlearn: 1.0746571\ttotal: 6h 59s\tremaining: 3h 36m 35s\n",
            "625:\tlearn: 1.0746008\ttotal: 6h 1m 30s\tremaining: 3h 35m 59s\n",
            "626:\tlearn: 1.0745589\ttotal: 6h 1m 59s\tremaining: 3h 35m 20s\n",
            "627:\tlearn: 1.0745414\ttotal: 6h 2m 34s\tremaining: 3h 34m 46s\n",
            "628:\tlearn: 1.0744954\ttotal: 6h 3m 13s\tremaining: 3h 34m 14s\n",
            "629:\tlearn: 1.0744398\ttotal: 6h 3m 43s\tremaining: 3h 33m 37s\n",
            "630:\tlearn: 1.0743707\ttotal: 6h 4m 14s\tremaining: 3h 33m\n",
            "631:\tlearn: 1.0743167\ttotal: 6h 4m 43s\tremaining: 3h 32m 22s\n",
            "632:\tlearn: 1.0742638\ttotal: 6h 5m 22s\tremaining: 3h 31m 50s\n",
            "633:\tlearn: 1.0742186\ttotal: 6h 5m 58s\tremaining: 3h 31m 16s\n",
            "634:\tlearn: 1.0741594\ttotal: 6h 6m 37s\tremaining: 3h 30m 44s\n",
            "635:\tlearn: 1.0741407\ttotal: 6h 7m 12s\tremaining: 3h 30m 9s\n",
            "636:\tlearn: 1.0740038\ttotal: 6h 7m 49s\tremaining: 3h 29m 36s\n",
            "637:\tlearn: 1.0739888\ttotal: 6h 8m 24s\tremaining: 3h 29m 2s\n",
            "638:\tlearn: 1.0739533\ttotal: 6h 8m 54s\tremaining: 3h 28m 24s\n",
            "639:\tlearn: 1.0738976\ttotal: 6h 9m 28s\tremaining: 3h 27m 49s\n",
            "640:\tlearn: 1.0738537\ttotal: 6h 9m 58s\tremaining: 3h 27m 12s\n",
            "641:\tlearn: 1.0738377\ttotal: 6h 10m 31s\tremaining: 3h 26m 36s\n",
            "642:\tlearn: 1.0738277\ttotal: 6h 11m 8s\tremaining: 3h 26m 3s\n",
            "643:\tlearn: 1.0738030\ttotal: 6h 11m 43s\tremaining: 3h 25m 29s\n",
            "644:\tlearn: 1.0737642\ttotal: 6h 12m 19s\tremaining: 3h 24m 55s\n",
            "645:\tlearn: 1.0737490\ttotal: 6h 12m 58s\tremaining: 3h 24m 22s\n",
            "646:\tlearn: 1.0737100\ttotal: 6h 13m 26s\tremaining: 3h 23m 45s\n",
            "647:\tlearn: 1.0736856\ttotal: 6h 14m 9s\tremaining: 3h 23m 14s\n",
            "648:\tlearn: 1.0736673\ttotal: 6h 14m 51s\tremaining: 3h 22m 44s\n",
            "649:\tlearn: 1.0736011\ttotal: 6h 15m 34s\tremaining: 3h 22m 13s\n",
            "650:\tlearn: 1.0735712\ttotal: 6h 16m 7s\tremaining: 3h 21m 38s\n",
            "651:\tlearn: 1.0735165\ttotal: 6h 16m 47s\tremaining: 3h 21m 6s\n",
            "652:\tlearn: 1.0734822\ttotal: 6h 17m 25s\tremaining: 3h 20m 33s\n",
            "653:\tlearn: 1.0734575\ttotal: 6h 17m 56s\tremaining: 3h 19m 56s\n",
            "654:\tlearn: 1.0734316\ttotal: 6h 18m 31s\tremaining: 3h 19m 22s\n",
            "655:\tlearn: 1.0733844\ttotal: 6h 19m 5s\tremaining: 3h 18m 47s\n",
            "656:\tlearn: 1.0733534\ttotal: 6h 19m 33s\tremaining: 3h 18m 9s\n",
            "657:\tlearn: 1.0732956\ttotal: 6h 20m 10s\tremaining: 3h 17m 36s\n",
            "658:\tlearn: 1.0732686\ttotal: 6h 20m 47s\tremaining: 3h 17m 2s\n",
            "659:\tlearn: 1.0732332\ttotal: 6h 21m 17s\tremaining: 3h 16m 25s\n",
            "660:\tlearn: 1.0731995\ttotal: 6h 22m 1s\tremaining: 3h 15m 55s\n",
            "661:\tlearn: 1.0731478\ttotal: 6h 22m 41s\tremaining: 3h 15m 23s\n",
            "662:\tlearn: 1.0731174\ttotal: 6h 23m 14s\tremaining: 3h 14m 48s\n",
            "663:\tlearn: 1.0730587\ttotal: 6h 23m 55s\tremaining: 3h 14m 16s\n",
            "664:\tlearn: 1.0728440\ttotal: 6h 24m 31s\tremaining: 3h 13m 42s\n",
            "665:\tlearn: 1.0728016\ttotal: 6h 25m 7s\tremaining: 3h 13m 8s\n",
            "666:\tlearn: 1.0727689\ttotal: 6h 25m 34s\tremaining: 3h 12m 30s\n",
            "667:\tlearn: 1.0727095\ttotal: 6h 26m 14s\tremaining: 3h 11m 57s\n",
            "668:\tlearn: 1.0725986\ttotal: 6h 26m 54s\tremaining: 3h 11m 25s\n",
            "669:\tlearn: 1.0725827\ttotal: 6h 27m 25s\tremaining: 3h 10m 49s\n",
            "670:\tlearn: 1.0725477\ttotal: 6h 27m 58s\tremaining: 3h 10m 13s\n",
            "671:\tlearn: 1.0724937\ttotal: 6h 28m 34s\tremaining: 3h 9m 39s\n",
            "672:\tlearn: 1.0724343\ttotal: 6h 29m 7s\tremaining: 3h 9m 4s\n",
            "673:\tlearn: 1.0723902\ttotal: 6h 29m 48s\tremaining: 3h 8m 32s\n",
            "674:\tlearn: 1.0723534\ttotal: 6h 30m 18s\tremaining: 3h 7m 55s\n",
            "675:\tlearn: 1.0722324\ttotal: 6h 30m 56s\tremaining: 3h 7m 22s\n",
            "676:\tlearn: 1.0721975\ttotal: 6h 31m 34s\tremaining: 3h 6m 49s\n",
            "677:\tlearn: 1.0721417\ttotal: 6h 32m 12s\tremaining: 3h 6m 16s\n",
            "678:\tlearn: 1.0720987\ttotal: 6h 32m 54s\tremaining: 3h 5m 44s\n",
            "679:\tlearn: 1.0720456\ttotal: 6h 33m 33s\tremaining: 3h 5m 12s\n",
            "680:\tlearn: 1.0719300\ttotal: 6h 34m 6s\tremaining: 3h 4m 36s\n",
            "681:\tlearn: 1.0718829\ttotal: 6h 34m 39s\tremaining: 3h 4m 1s\n",
            "682:\tlearn: 1.0718306\ttotal: 6h 35m 17s\tremaining: 3h 3m 28s\n",
            "683:\tlearn: 1.0717926\ttotal: 6h 35m 55s\tremaining: 3h 2m 54s\n",
            "684:\tlearn: 1.0717436\ttotal: 6h 36m 35s\tremaining: 3h 2m 22s\n",
            "685:\tlearn: 1.0717167\ttotal: 6h 37m 10s\tremaining: 3h 1m 47s\n",
            "686:\tlearn: 1.0716856\ttotal: 6h 37m 38s\tremaining: 3h 1m 10s\n",
            "687:\tlearn: 1.0716497\ttotal: 6h 38m 15s\tremaining: 3h 36s\n",
            "688:\tlearn: 1.0716319\ttotal: 6h 38m 58s\tremaining: 3h 5s\n",
            "689:\tlearn: 1.0715903\ttotal: 6h 39m 35s\tremaining: 2h 59m 31s\n",
            "690:\tlearn: 1.0715479\ttotal: 6h 40m 11s\tremaining: 2h 58m 57s\n",
            "691:\tlearn: 1.0714975\ttotal: 6h 40m 45s\tremaining: 2h 58m 22s\n",
            "692:\tlearn: 1.0714597\ttotal: 6h 41m 15s\tremaining: 2h 57m 45s\n",
            "693:\tlearn: 1.0713241\ttotal: 6h 41m 50s\tremaining: 2h 57m 10s\n",
            "694:\tlearn: 1.0712838\ttotal: 6h 42m 28s\tremaining: 2h 56m 37s\n",
            "695:\tlearn: 1.0712650\ttotal: 6h 43m 1s\tremaining: 2h 56m 1s\n",
            "696:\tlearn: 1.0712458\ttotal: 6h 43m 35s\tremaining: 2h 55m 26s\n",
            "697:\tlearn: 1.0711935\ttotal: 6h 44m 10s\tremaining: 2h 54m 52s\n",
            "698:\tlearn: 1.0711694\ttotal: 6h 44m 47s\tremaining: 2h 54m 18s\n",
            "699:\tlearn: 1.0710505\ttotal: 6h 45m 23s\tremaining: 2h 53m 44s\n",
            "700:\tlearn: 1.0710315\ttotal: 6h 46m 1s\tremaining: 2h 53m 10s\n",
            "701:\tlearn: 1.0709790\ttotal: 6h 46m 34s\tremaining: 2h 52m 35s\n",
            "702:\tlearn: 1.0709241\ttotal: 6h 47m 8s\tremaining: 2h 52m\n",
            "703:\tlearn: 1.0709006\ttotal: 6h 47m 37s\tremaining: 2h 51m 23s\n",
            "704:\tlearn: 1.0708702\ttotal: 6h 48m 5s\tremaining: 2h 50m 45s\n",
            "705:\tlearn: 1.0708258\ttotal: 6h 48m 37s\tremaining: 2h 50m 10s\n",
            "706:\tlearn: 1.0707917\ttotal: 6h 49m 12s\tremaining: 2h 49m 35s\n",
            "707:\tlearn: 1.0707456\ttotal: 6h 49m 46s\tremaining: 2h 49m\n",
            "708:\tlearn: 1.0707198\ttotal: 6h 50m 29s\tremaining: 2h 48m 28s\n",
            "709:\tlearn: 1.0706924\ttotal: 6h 51m 4s\tremaining: 2h 47m 54s\n",
            "710:\tlearn: 1.0706505\ttotal: 6h 51m 33s\tremaining: 2h 47m 17s\n",
            "711:\tlearn: 1.0706312\ttotal: 6h 52m 10s\tremaining: 2h 46m 43s\n",
            "712:\tlearn: 1.0705937\ttotal: 6h 52m 47s\tremaining: 2h 46m 9s\n",
            "713:\tlearn: 1.0705326\ttotal: 6h 53m 22s\tremaining: 2h 45m 34s\n",
            "714:\tlearn: 1.0705162\ttotal: 6h 53m 51s\tremaining: 2h 44m 57s\n",
            "715:\tlearn: 1.0704792\ttotal: 6h 54m 33s\tremaining: 2h 44m 26s\n",
            "716:\tlearn: 1.0704438\ttotal: 6h 55m 12s\tremaining: 2h 43m 52s\n",
            "717:\tlearn: 1.0704118\ttotal: 6h 55m 47s\tremaining: 2h 43m 18s\n",
            "718:\tlearn: 1.0703882\ttotal: 6h 56m 23s\tremaining: 2h 42m 44s\n",
            "719:\tlearn: 1.0703552\ttotal: 6h 56m 55s\tremaining: 2h 42m 8s\n",
            "720:\tlearn: 1.0702749\ttotal: 6h 57m 36s\tremaining: 2h 41m 36s\n",
            "721:\tlearn: 1.0702540\ttotal: 6h 58m 11s\tremaining: 2h 41m 1s\n",
            "722:\tlearn: 1.0702256\ttotal: 6h 58m 47s\tremaining: 2h 40m 27s\n",
            "723:\tlearn: 1.0702020\ttotal: 6h 59m 19s\tremaining: 2h 39m 51s\n",
            "724:\tlearn: 1.0701761\ttotal: 7h\tremaining: 2h 39m 18s\n",
            "725:\tlearn: 1.0701261\ttotal: 7h 43s\tremaining: 2h 38m 47s\n",
            "726:\tlearn: 1.0700331\ttotal: 7h 1m 18s\tremaining: 2h 38m 12s\n",
            "727:\tlearn: 1.0700047\ttotal: 7h 1m 55s\tremaining: 2h 37m 38s\n",
            "728:\tlearn: 1.0699764\ttotal: 7h 2m 24s\tremaining: 2h 37m 1s\n",
            "729:\tlearn: 1.0699264\ttotal: 7h 2m 53s\tremaining: 2h 36m 24s\n",
            "730:\tlearn: 1.0698808\ttotal: 7h 3m 28s\tremaining: 2h 35m 50s\n",
            "731:\tlearn: 1.0698477\ttotal: 7h 4m 5s\tremaining: 2h 35m 16s\n",
            "732:\tlearn: 1.0698189\ttotal: 7h 4m 40s\tremaining: 2h 34m 41s\n",
            "733:\tlearn: 1.0697994\ttotal: 7h 5m 12s\tremaining: 2h 34m 5s\n",
            "734:\tlearn: 1.0697527\ttotal: 7h 5m 53s\tremaining: 2h 33m 33s\n",
            "735:\tlearn: 1.0697311\ttotal: 7h 6m 31s\tremaining: 2h 32m 59s\n",
            "736:\tlearn: 1.0697003\ttotal: 7h 7m 11s\tremaining: 2h 32m 26s\n",
            "737:\tlearn: 1.0696847\ttotal: 7h 7m 51s\tremaining: 2h 31m 53s\n",
            "738:\tlearn: 1.0696197\ttotal: 7h 8m 30s\tremaining: 2h 31m 20s\n",
            "739:\tlearn: 1.0695751\ttotal: 7h 9m 11s\tremaining: 2h 30m 47s\n",
            "740:\tlearn: 1.0695589\ttotal: 7h 9m 42s\tremaining: 2h 30m 11s\n",
            "741:\tlearn: 1.0695435\ttotal: 7h 10m 16s\tremaining: 2h 29m 36s\n",
            "742:\tlearn: 1.0695079\ttotal: 7h 10m 47s\tremaining: 2h 29m\n",
            "743:\tlearn: 1.0694725\ttotal: 7h 11m 26s\tremaining: 2h 28m 27s\n",
            "744:\tlearn: 1.0694571\ttotal: 7h 12m 5s\tremaining: 2h 27m 53s\n",
            "745:\tlearn: 1.0694197\ttotal: 7h 12m 41s\tremaining: 2h 27m 19s\n",
            "746:\tlearn: 1.0693916\ttotal: 7h 13m 16s\tremaining: 2h 26m 44s\n",
            "747:\tlearn: 1.0693375\ttotal: 7h 13m 50s\tremaining: 2h 26m 9s\n",
            "748:\tlearn: 1.0693158\ttotal: 7h 14m 27s\tremaining: 2h 25m 35s\n",
            "749:\tlearn: 1.0692404\ttotal: 7h 15m 9s\tremaining: 2h 25m 3s\n",
            "750:\tlearn: 1.0692069\ttotal: 7h 15m 46s\tremaining: 2h 24m 29s\n",
            "751:\tlearn: 1.0691612\ttotal: 7h 16m 29s\tremaining: 2h 23m 56s\n",
            "752:\tlearn: 1.0691387\ttotal: 7h 17m 11s\tremaining: 2h 23m 24s\n",
            "753:\tlearn: 1.0690983\ttotal: 7h 17m 44s\tremaining: 2h 22m 49s\n",
            "754:\tlearn: 1.0690517\ttotal: 7h 18m 26s\tremaining: 2h 22m 16s\n",
            "755:\tlearn: 1.0690203\ttotal: 7h 18m 58s\tremaining: 2h 21m 40s\n",
            "756:\tlearn: 1.0689723\ttotal: 7h 19m 27s\tremaining: 2h 21m 4s\n",
            "757:\tlearn: 1.0689420\ttotal: 7h 19m 54s\tremaining: 2h 20m 26s\n",
            "758:\tlearn: 1.0689195\ttotal: 7h 20m 24s\tremaining: 2h 19m 50s\n",
            "759:\tlearn: 1.0688863\ttotal: 7h 20m 56s\tremaining: 2h 19m 14s\n",
            "760:\tlearn: 1.0687361\ttotal: 7h 21m 32s\tremaining: 2h 18m 40s\n",
            "761:\tlearn: 1.0686779\ttotal: 7h 22m 3s\tremaining: 2h 18m 4s\n",
            "762:\tlearn: 1.0686249\ttotal: 7h 22m 43s\tremaining: 2h 17m 31s\n",
            "763:\tlearn: 1.0686017\ttotal: 7h 23m 19s\tremaining: 2h 16m 56s\n",
            "764:\tlearn: 1.0685627\ttotal: 7h 23m 57s\tremaining: 2h 16m 22s\n",
            "765:\tlearn: 1.0685228\ttotal: 7h 24m 30s\tremaining: 2h 15m 47s\n",
            "766:\tlearn: 1.0684878\ttotal: 7h 25m\tremaining: 2h 15m 11s\n",
            "767:\tlearn: 1.0684584\ttotal: 7h 25m 37s\tremaining: 2h 14m 36s\n",
            "768:\tlearn: 1.0684318\ttotal: 7h 26m 8s\tremaining: 2h 14m\n",
            "769:\tlearn: 1.0684021\ttotal: 7h 26m 51s\tremaining: 2h 13m 28s\n",
            "770:\tlearn: 1.0683226\ttotal: 7h 27m 32s\tremaining: 2h 12m 55s\n",
            "771:\tlearn: 1.0683037\ttotal: 7h 28m 5s\tremaining: 2h 12m 20s\n",
            "772:\tlearn: 1.0682759\ttotal: 7h 28m 39s\tremaining: 2h 11m 45s\n",
            "773:\tlearn: 1.0681999\ttotal: 7h 29m 19s\tremaining: 2h 11m 11s\n",
            "774:\tlearn: 1.0681621\ttotal: 7h 29m 54s\tremaining: 2h 10m 37s\n",
            "775:\tlearn: 1.0681291\ttotal: 7h 30m 33s\tremaining: 2h 10m 3s\n",
            "776:\tlearn: 1.0680048\ttotal: 7h 31m 15s\tremaining: 2h 9m 30s\n",
            "777:\tlearn: 1.0679802\ttotal: 7h 31m 50s\tremaining: 2h 8m 55s\n",
            "778:\tlearn: 1.0679556\ttotal: 7h 32m 24s\tremaining: 2h 8m 20s\n",
            "779:\tlearn: 1.0678881\ttotal: 7h 33m 1s\tremaining: 2h 7m 46s\n",
            "780:\tlearn: 1.0678526\ttotal: 7h 33m 46s\tremaining: 2h 7m 14s\n",
            "781:\tlearn: 1.0678176\ttotal: 7h 34m 17s\tremaining: 2h 6m 38s\n",
            "782:\tlearn: 1.0677770\ttotal: 7h 34m 59s\tremaining: 2h 6m 5s\n",
            "783:\tlearn: 1.0677251\ttotal: 7h 35m 41s\tremaining: 2h 5m 32s\n",
            "784:\tlearn: 1.0677079\ttotal: 7h 36m 20s\tremaining: 2h 4m 59s\n",
            "785:\tlearn: 1.0676842\ttotal: 7h 36m 53s\tremaining: 2h 4m 23s\n",
            "786:\tlearn: 1.0676427\ttotal: 7h 37m 28s\tremaining: 2h 3m 48s\n",
            "787:\tlearn: 1.0676196\ttotal: 7h 38m 5s\tremaining: 2h 3m 14s\n",
            "788:\tlearn: 1.0675694\ttotal: 7h 38m 38s\tremaining: 2h 2m 39s\n",
            "789:\tlearn: 1.0675199\ttotal: 7h 39m 12s\tremaining: 2h 2m 4s\n",
            "790:\tlearn: 1.0674983\ttotal: 7h 39m 45s\tremaining: 2h 1m 28s\n",
            "791:\tlearn: 1.0674688\ttotal: 7h 40m 14s\tremaining: 2h 52s\n",
            "792:\tlearn: 1.0674414\ttotal: 7h 40m 51s\tremaining: 2h 17s\n",
            "793:\tlearn: 1.0673503\ttotal: 7h 41m 27s\tremaining: 1h 59m 43s\n",
            "794:\tlearn: 1.0672510\ttotal: 7h 42m 3s\tremaining: 1h 59m 8s\n",
            "795:\tlearn: 1.0672003\ttotal: 7h 42m 38s\tremaining: 1h 58m 34s\n",
            "796:\tlearn: 1.0671682\ttotal: 7h 43m 12s\tremaining: 1h 57m 58s\n",
            "797:\tlearn: 1.0671487\ttotal: 7h 43m 45s\tremaining: 1h 57m 23s\n",
            "798:\tlearn: 1.0671249\ttotal: 7h 44m 18s\tremaining: 1h 56m 48s\n",
            "799:\tlearn: 1.0670991\ttotal: 7h 44m 52s\tremaining: 1h 56m 13s\n",
            "800:\tlearn: 1.0670798\ttotal: 7h 45m 29s\tremaining: 1h 55m 38s\n",
            "801:\tlearn: 1.0670376\ttotal: 7h 46m 11s\tremaining: 1h 55m 5s\n",
            "802:\tlearn: 1.0670147\ttotal: 7h 46m 42s\tremaining: 1h 54m 29s\n",
            "803:\tlearn: 1.0669831\ttotal: 7h 47m 17s\tremaining: 1h 53m 55s\n",
            "804:\tlearn: 1.0669712\ttotal: 7h 47m 50s\tremaining: 1h 53m 19s\n",
            "805:\tlearn: 1.0669350\ttotal: 7h 48m 20s\tremaining: 1h 52m 43s\n",
            "806:\tlearn: 1.0669063\ttotal: 7h 48m 53s\tremaining: 1h 52m 8s\n",
            "807:\tlearn: 1.0668458\ttotal: 7h 49m 31s\tremaining: 1h 51m 34s\n",
            "808:\tlearn: 1.0668136\ttotal: 7h 50m 7s\tremaining: 1h 50m 59s\n",
            "809:\tlearn: 1.0667796\ttotal: 7h 50m 41s\tremaining: 1h 50m 24s\n",
            "810:\tlearn: 1.0667189\ttotal: 7h 51m 18s\tremaining: 1h 49m 50s\n",
            "811:\tlearn: 1.0666626\ttotal: 7h 51m 57s\tremaining: 1h 49m 16s\n",
            "812:\tlearn: 1.0666344\ttotal: 7h 52m 26s\tremaining: 1h 48m 40s\n",
            "813:\tlearn: 1.0665738\ttotal: 7h 53m 8s\tremaining: 1h 48m 6s\n",
            "814:\tlearn: 1.0664780\ttotal: 7h 53m 45s\tremaining: 1h 47m 32s\n",
            "815:\tlearn: 1.0664345\ttotal: 7h 54m 24s\tremaining: 1h 46m 58s\n",
            "816:\tlearn: 1.0663138\ttotal: 7h 55m\tremaining: 1h 46m 23s\n",
            "817:\tlearn: 1.0662826\ttotal: 7h 55m 31s\tremaining: 1h 45m 48s\n",
            "818:\tlearn: 1.0662461\ttotal: 7h 56m 10s\tremaining: 1h 45m 14s\n",
            "819:\tlearn: 1.0662317\ttotal: 7h 56m 47s\tremaining: 1h 44m 39s\n",
            "820:\tlearn: 1.0662204\ttotal: 7h 57m 16s\tremaining: 1h 44m 3s\n",
            "821:\tlearn: 1.0661765\ttotal: 7h 57m 52s\tremaining: 1h 43m 28s\n",
            "822:\tlearn: 1.0661327\ttotal: 7h 58m 24s\tremaining: 1h 42m 53s\n",
            "823:\tlearn: 1.0661127\ttotal: 7h 58m 55s\tremaining: 1h 42m 17s\n",
            "824:\tlearn: 1.0660823\ttotal: 7h 59m 26s\tremaining: 1h 41m 41s\n",
            "825:\tlearn: 1.0660473\ttotal: 8h 5s\tremaining: 1h 41m 7s\n",
            "826:\tlearn: 1.0660193\ttotal: 8h 37s\tremaining: 1h 40m 32s\n",
            "827:\tlearn: 1.0659828\ttotal: 8h 1m 17s\tremaining: 1h 39m 58s\n",
            "828:\tlearn: 1.0659433\ttotal: 8h 1m 50s\tremaining: 1h 39m 23s\n",
            "829:\tlearn: 1.0659025\ttotal: 8h 2m 26s\tremaining: 1h 38m 48s\n",
            "830:\tlearn: 1.0658537\ttotal: 8h 3m 4s\tremaining: 1h 38m 14s\n",
            "831:\tlearn: 1.0658173\ttotal: 8h 3m 42s\tremaining: 1h 37m 40s\n",
            "832:\tlearn: 1.0657689\ttotal: 8h 4m 23s\tremaining: 1h 37m 6s\n",
            "833:\tlearn: 1.0657571\ttotal: 8h 4m 56s\tremaining: 1h 36m 31s\n",
            "834:\tlearn: 1.0657220\ttotal: 8h 5m 25s\tremaining: 1h 35m 55s\n",
            "835:\tlearn: 1.0656757\ttotal: 8h 5m 57s\tremaining: 1h 35m 19s\n",
            "836:\tlearn: 1.0656361\ttotal: 8h 6m 27s\tremaining: 1h 34m 44s\n",
            "837:\tlearn: 1.0655893\ttotal: 8h 6m 54s\tremaining: 1h 34m 7s\n",
            "838:\tlearn: 1.0655338\ttotal: 8h 7m 35s\tremaining: 1h 33m 33s\n",
            "839:\tlearn: 1.0655099\ttotal: 8h 8m 12s\tremaining: 1h 32m 59s\n",
            "840:\tlearn: 1.0654979\ttotal: 8h 8m 47s\tremaining: 1h 32m 24s\n",
            "841:\tlearn: 1.0654488\ttotal: 8h 9m 29s\tremaining: 1h 31m 51s\n",
            "842:\tlearn: 1.0654166\ttotal: 8h 9m 58s\tremaining: 1h 31m 15s\n",
            "843:\tlearn: 1.0653949\ttotal: 8h 10m 29s\tremaining: 1h 30m 39s\n",
            "844:\tlearn: 1.0653691\ttotal: 8h 11m 7s\tremaining: 1h 30m 5s\n",
            "845:\tlearn: 1.0653421\ttotal: 8h 11m 39s\tremaining: 1h 29m 29s\n",
            "846:\tlearn: 1.0653125\ttotal: 8h 12m 19s\tremaining: 1h 28m 56s\n",
            "847:\tlearn: 1.0652945\ttotal: 8h 13m 1s\tremaining: 1h 28m 22s\n",
            "848:\tlearn: 1.0652605\ttotal: 8h 13m 41s\tremaining: 1h 27m 48s\n",
            "849:\tlearn: 1.0652391\ttotal: 8h 14m 21s\tremaining: 1h 27m 14s\n",
            "850:\tlearn: 1.0651139\ttotal: 8h 14m 58s\tremaining: 1h 26m 39s\n",
            "851:\tlearn: 1.0650867\ttotal: 8h 15m 31s\tremaining: 1h 26m 4s\n",
            "852:\tlearn: 1.0650624\ttotal: 8h 15m 59s\tremaining: 1h 25m 28s\n",
            "853:\tlearn: 1.0650283\ttotal: 8h 16m 39s\tremaining: 1h 24m 54s\n",
            "854:\tlearn: 1.0650061\ttotal: 8h 17m 18s\tremaining: 1h 24m 20s\n",
            "855:\tlearn: 1.0649753\ttotal: 8h 17m 50s\tremaining: 1h 23m 44s\n",
            "856:\tlearn: 1.0649480\ttotal: 8h 18m 28s\tremaining: 1h 23m 10s\n",
            "857:\tlearn: 1.0649015\ttotal: 8h 19m 8s\tremaining: 1h 22m 36s\n",
            "858:\tlearn: 1.0648479\ttotal: 8h 19m 41s\tremaining: 1h 22m 1s\n",
            "859:\tlearn: 1.0648117\ttotal: 8h 20m 19s\tremaining: 1h 21m 26s\n",
            "860:\tlearn: 1.0647506\ttotal: 8h 20m 53s\tremaining: 1h 20m 51s\n",
            "861:\tlearn: 1.0647137\ttotal: 8h 21m 26s\tremaining: 1h 20m 16s\n",
            "862:\tlearn: 1.0646657\ttotal: 8h 22m 6s\tremaining: 1h 19m 42s\n",
            "863:\tlearn: 1.0645620\ttotal: 8h 22m 45s\tremaining: 1h 19m 8s\n",
            "864:\tlearn: 1.0645296\ttotal: 8h 23m 23s\tremaining: 1h 18m 33s\n",
            "865:\tlearn: 1.0644825\ttotal: 8h 23m 57s\tremaining: 1h 17m 58s\n",
            "866:\tlearn: 1.0644655\ttotal: 8h 24m 31s\tremaining: 1h 17m 23s\n",
            "867:\tlearn: 1.0644348\ttotal: 8h 25m 2s\tremaining: 1h 16m 48s\n",
            "868:\tlearn: 1.0643963\ttotal: 8h 25m 40s\tremaining: 1h 16m 13s\n",
            "869:\tlearn: 1.0643694\ttotal: 8h 26m 14s\tremaining: 1h 15m 38s\n",
            "870:\tlearn: 1.0643239\ttotal: 8h 26m 48s\tremaining: 1h 15m 3s\n",
            "871:\tlearn: 1.0642430\ttotal: 8h 27m 25s\tremaining: 1h 14m 29s\n",
            "872:\tlearn: 1.0642138\ttotal: 8h 27m 59s\tremaining: 1h 13m 54s\n",
            "873:\tlearn: 1.0641670\ttotal: 8h 28m 41s\tremaining: 1h 13m 20s\n",
            "874:\tlearn: 1.0641490\ttotal: 8h 29m 24s\tremaining: 1h 12m 46s\n",
            "875:\tlearn: 1.0641113\ttotal: 8h 30m 3s\tremaining: 1h 12m 12s\n",
            "876:\tlearn: 1.0640758\ttotal: 8h 30m 39s\tremaining: 1h 11m 37s\n",
            "877:\tlearn: 1.0640602\ttotal: 8h 31m 16s\tremaining: 1h 11m 2s\n",
            "878:\tlearn: 1.0640093\ttotal: 8h 31m 46s\tremaining: 1h 10m 26s\n",
            "879:\tlearn: 1.0639812\ttotal: 8h 32m 19s\tremaining: 1h 9m 51s\n",
            "880:\tlearn: 1.0639560\ttotal: 8h 32m 48s\tremaining: 1h 9m 16s\n",
            "881:\tlearn: 1.0639006\ttotal: 8h 33m 22s\tremaining: 1h 8m 41s\n",
            "882:\tlearn: 1.0638568\ttotal: 8h 33m 52s\tremaining: 1h 8m 5s\n",
            "883:\tlearn: 1.0638248\ttotal: 8h 34m 28s\tremaining: 1h 7m 30s\n",
            "884:\tlearn: 1.0637947\ttotal: 8h 34m 57s\tremaining: 1h 6m 54s\n",
            "885:\tlearn: 1.0637731\ttotal: 8h 35m 31s\tremaining: 1h 6m 19s\n",
            "886:\tlearn: 1.0637302\ttotal: 8h 36m 13s\tremaining: 1h 5m 45s\n",
            "887:\tlearn: 1.0637036\ttotal: 8h 36m 43s\tremaining: 1h 5m 10s\n",
            "888:\tlearn: 1.0636697\ttotal: 8h 37m 24s\tremaining: 1h 4m 36s\n",
            "889:\tlearn: 1.0636438\ttotal: 8h 37m 57s\tremaining: 1h 4m\n",
            "890:\tlearn: 1.0635735\ttotal: 8h 38m 37s\tremaining: 1h 3m 26s\n",
            "891:\tlearn: 1.0635044\ttotal: 8h 39m 6s\tremaining: 1h 2m 51s\n",
            "892:\tlearn: 1.0634924\ttotal: 8h 39m 47s\tremaining: 1h 2m 16s\n",
            "893:\tlearn: 1.0634778\ttotal: 8h 40m 23s\tremaining: 1h 1m 42s\n",
            "894:\tlearn: 1.0634304\ttotal: 8h 41m 6s\tremaining: 1h 1m 8s\n",
            "895:\tlearn: 1.0634084\ttotal: 8h 41m 40s\tremaining: 1h 33s\n",
            "896:\tlearn: 1.0633652\ttotal: 8h 42m 22s\tremaining: 59m 58s\n",
            "897:\tlearn: 1.0633073\ttotal: 8h 43m 4s\tremaining: 59m 24s\n",
            "898:\tlearn: 1.0632864\ttotal: 8h 43m 35s\tremaining: 58m 49s\n",
            "899:\tlearn: 1.0632417\ttotal: 8h 44m 14s\tremaining: 58m 14s\n",
            "900:\tlearn: 1.0632302\ttotal: 8h 44m 54s\tremaining: 57m 40s\n",
            "901:\tlearn: 1.0631907\ttotal: 8h 45m 30s\tremaining: 57m 5s\n",
            "902:\tlearn: 1.0631664\ttotal: 8h 46m 10s\tremaining: 56m 31s\n",
            "903:\tlearn: 1.0631496\ttotal: 8h 46m 39s\tremaining: 55m 55s\n",
            "904:\tlearn: 1.0631156\ttotal: 8h 47m 20s\tremaining: 55m 21s\n",
            "905:\tlearn: 1.0630559\ttotal: 8h 47m 55s\tremaining: 54m 46s\n",
            "906:\tlearn: 1.0629993\ttotal: 8h 48m 35s\tremaining: 54m 11s\n",
            "907:\tlearn: 1.0629579\ttotal: 8h 49m 9s\tremaining: 53m 36s\n",
            "908:\tlearn: 1.0629289\ttotal: 8h 49m 43s\tremaining: 53m 1s\n",
            "909:\tlearn: 1.0629004\ttotal: 8h 50m 23s\tremaining: 52m 27s\n",
            "910:\tlearn: 1.0628833\ttotal: 8h 50m 58s\tremaining: 51m 52s\n",
            "911:\tlearn: 1.0628529\ttotal: 8h 51m 32s\tremaining: 51m 17s\n",
            "912:\tlearn: 1.0628024\ttotal: 8h 52m 12s\tremaining: 50m 42s\n",
            "913:\tlearn: 1.0627797\ttotal: 8h 52m 45s\tremaining: 50m 7s\n",
            "914:\tlearn: 1.0627700\ttotal: 8h 53m 22s\tremaining: 49m 32s\n",
            "915:\tlearn: 1.0627491\ttotal: 8h 54m 2s\tremaining: 48m 58s\n",
            "916:\tlearn: 1.0627304\ttotal: 8h 54m 36s\tremaining: 48m 23s\n",
            "917:\tlearn: 1.0627048\ttotal: 8h 55m 15s\tremaining: 47m 48s\n",
            "918:\tlearn: 1.0626646\ttotal: 8h 55m 47s\tremaining: 47m 13s\n",
            "919:\tlearn: 1.0626241\ttotal: 8h 56m 26s\tremaining: 46m 38s\n",
            "920:\tlearn: 1.0625780\ttotal: 8h 56m 59s\tremaining: 46m 3s\n",
            "921:\tlearn: 1.0625373\ttotal: 8h 57m 40s\tremaining: 45m 29s\n",
            "922:\tlearn: 1.0624890\ttotal: 8h 58m 15s\tremaining: 44m 54s\n",
            "923:\tlearn: 1.0624782\ttotal: 8h 58m 56s\tremaining: 44m 19s\n",
            "924:\tlearn: 1.0624514\ttotal: 8h 59m 32s\tremaining: 43m 44s\n",
            "925:\tlearn: 1.0623671\ttotal: 9h 7s\tremaining: 43m 9s\n",
            "926:\tlearn: 1.0623575\ttotal: 9h 41s\tremaining: 42m 34s\n",
            "927:\tlearn: 1.0623089\ttotal: 9h 1m 21s\tremaining: 42m\n",
            "928:\tlearn: 1.0622832\ttotal: 9h 1m 53s\tremaining: 41m 24s\n",
            "929:\tlearn: 1.0622683\ttotal: 9h 2m 26s\tremaining: 40m 49s\n",
            "930:\tlearn: 1.0622259\ttotal: 9h 3m 6s\tremaining: 40m 15s\n",
            "931:\tlearn: 1.0621887\ttotal: 9h 3m 41s\tremaining: 39m 40s\n",
            "932:\tlearn: 1.0621385\ttotal: 9h 4m 23s\tremaining: 39m 5s\n",
            "933:\tlearn: 1.0620785\ttotal: 9h 5m 1s\tremaining: 38m 30s\n",
            "934:\tlearn: 1.0620344\ttotal: 9h 5m 39s\tremaining: 37m 55s\n",
            "935:\tlearn: 1.0619981\ttotal: 9h 6m 19s\tremaining: 37m 21s\n",
            "936:\tlearn: 1.0619543\ttotal: 9h 6m 55s\tremaining: 36m 46s\n",
            "937:\tlearn: 1.0619317\ttotal: 9h 7m 37s\tremaining: 36m 11s\n",
            "938:\tlearn: 1.0619061\ttotal: 9h 8m 18s\tremaining: 35m 37s\n",
            "939:\tlearn: 1.0618817\ttotal: 9h 8m 51s\tremaining: 35m 2s\n",
            "940:\tlearn: 1.0618286\ttotal: 9h 9m 25s\tremaining: 34m 26s\n",
            "941:\tlearn: 1.0617833\ttotal: 9h 10m 6s\tremaining: 33m 52s\n",
            "942:\tlearn: 1.0617442\ttotal: 9h 10m 38s\tremaining: 33m 17s\n",
            "943:\tlearn: 1.0616996\ttotal: 9h 11m 13s\tremaining: 32m 41s\n",
            "944:\tlearn: 1.0616217\ttotal: 9h 11m 50s\tremaining: 32m 7s\n",
            "945:\tlearn: 1.0615722\ttotal: 9h 12m 24s\tremaining: 31m 31s\n",
            "946:\tlearn: 1.0615258\ttotal: 9h 13m 3s\tremaining: 30m 57s\n",
            "947:\tlearn: 1.0614862\ttotal: 9h 13m 42s\tremaining: 30m 22s\n",
            "948:\tlearn: 1.0614584\ttotal: 9h 14m 17s\tremaining: 29m 47s\n",
            "949:\tlearn: 1.0614286\ttotal: 9h 14m 42s\tremaining: 29m 11s\n",
            "950:\tlearn: 1.0613807\ttotal: 9h 15m 25s\tremaining: 28m 37s\n",
            "951:\tlearn: 1.0613487\ttotal: 9h 15m 53s\tremaining: 28m 1s\n",
            "952:\tlearn: 1.0612685\ttotal: 9h 16m 32s\tremaining: 27m 26s\n",
            "953:\tlearn: 1.0612345\ttotal: 9h 17m 3s\tremaining: 26m 51s\n",
            "954:\tlearn: 1.0612105\ttotal: 9h 17m 39s\tremaining: 26m 16s\n",
            "955:\tlearn: 1.0611790\ttotal: 9h 18m 12s\tremaining: 25m 41s\n",
            "956:\tlearn: 1.0611375\ttotal: 9h 18m 56s\tremaining: 25m 6s\n",
            "957:\tlearn: 1.0611186\ttotal: 9h 19m 34s\tremaining: 24m 31s\n",
            "958:\tlearn: 1.0610931\ttotal: 9h 20m 4s\tremaining: 23m 56s\n",
            "959:\tlearn: 1.0610441\ttotal: 9h 20m 43s\tremaining: 23m 21s\n",
            "960:\tlearn: 1.0609800\ttotal: 9h 21m 22s\tremaining: 22m 46s\n",
            "961:\tlearn: 1.0609582\ttotal: 9h 22m\tremaining: 22m 12s\n",
            "962:\tlearn: 1.0609180\ttotal: 9h 22m 33s\tremaining: 21m 36s\n",
            "963:\tlearn: 1.0608779\ttotal: 9h 23m 9s\tremaining: 21m 1s\n",
            "964:\tlearn: 1.0608407\ttotal: 9h 23m 52s\tremaining: 20m 27s\n",
            "965:\tlearn: 1.0608243\ttotal: 9h 24m 29s\tremaining: 19m 52s\n",
            "966:\tlearn: 1.0607981\ttotal: 9h 25m 10s\tremaining: 19m 17s\n",
            "967:\tlearn: 1.0607711\ttotal: 9h 25m 52s\tremaining: 18m 42s\n",
            "968:\tlearn: 1.0607328\ttotal: 9h 26m 28s\tremaining: 18m 7s\n",
            "969:\tlearn: 1.0607146\ttotal: 9h 27m 4s\tremaining: 17m 32s\n",
            "970:\tlearn: 1.0606904\ttotal: 9h 27m 44s\tremaining: 16m 57s\n",
            "971:\tlearn: 1.0606632\ttotal: 9h 28m 26s\tremaining: 16m 22s\n",
            "972:\tlearn: 1.0606292\ttotal: 9h 29m 3s\tremaining: 15m 47s\n",
            "973:\tlearn: 1.0606168\ttotal: 9h 29m 36s\tremaining: 15m 12s\n",
            "974:\tlearn: 1.0605776\ttotal: 9h 30m 9s\tremaining: 14m 37s\n",
            "975:\tlearn: 1.0605565\ttotal: 9h 30m 42s\tremaining: 14m 2s\n",
            "976:\tlearn: 1.0605415\ttotal: 9h 31m 13s\tremaining: 13m 26s\n",
            "977:\tlearn: 1.0604926\ttotal: 9h 31m 46s\tremaining: 12m 51s\n",
            "978:\tlearn: 1.0604687\ttotal: 9h 32m 23s\tremaining: 12m 16s\n",
            "979:\tlearn: 1.0604309\ttotal: 9h 32m 58s\tremaining: 11m 41s\n",
            "980:\tlearn: 1.0604132\ttotal: 9h 33m 30s\tremaining: 11m 6s\n",
            "981:\tlearn: 1.0603762\ttotal: 9h 34m 5s\tremaining: 10m 31s\n",
            "982:\tlearn: 1.0602364\ttotal: 9h 34m 48s\tremaining: 9m 56s\n",
            "983:\tlearn: 1.0602197\ttotal: 9h 35m 28s\tremaining: 9m 21s\n",
            "984:\tlearn: 1.0602013\ttotal: 9h 36m 3s\tremaining: 8m 46s\n",
            "985:\tlearn: 1.0601596\ttotal: 9h 36m 41s\tremaining: 8m 11s\n",
            "986:\tlearn: 1.0601056\ttotal: 9h 37m 17s\tremaining: 7m 36s\n",
            "987:\tlearn: 1.0600841\ttotal: 9h 37m 48s\tremaining: 7m 1s\n",
            "988:\tlearn: 1.0600468\ttotal: 9h 38m 19s\tremaining: 6m 25s\n",
            "989:\tlearn: 1.0600181\ttotal: 9h 38m 50s\tremaining: 5m 50s\n",
            "990:\tlearn: 1.0599841\ttotal: 9h 39m 20s\tremaining: 5m 15s\n",
            "991:\tlearn: 1.0599417\ttotal: 9h 40m 2s\tremaining: 4m 40s\n",
            "992:\tlearn: 1.0599194\ttotal: 9h 40m 45s\tremaining: 4m 5s\n",
            "993:\tlearn: 1.0598818\ttotal: 9h 41m 25s\tremaining: 3m 30s\n",
            "994:\tlearn: 1.0598532\ttotal: 9h 42m 5s\tremaining: 2m 55s\n",
            "995:\tlearn: 1.0597587\ttotal: 9h 42m 41s\tremaining: 2m 20s\n",
            "996:\tlearn: 1.0597232\ttotal: 9h 43m 11s\tremaining: 1m 45s\n",
            "997:\tlearn: 1.0596916\ttotal: 9h 43m 51s\tremaining: 1m 10s\n",
            "998:\tlearn: 1.0596754\ttotal: 9h 44m 28s\tremaining: 35.1s\n",
            "999:\tlearn: 1.0596355\ttotal: 9h 44m 57s\tremaining: 0us\n",
            "[[0]\n",
            " [0]\n",
            " [0]\n",
            " ...\n",
            " [0]\n",
            " [0]\n",
            " [0]]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dg4si4utcNw6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "!cp *.csv /content/drive/\"My Drive\"/bookrating   "
      ],
      "execution_count": 66,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "M3L64QC0cN0m",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "p=preds_class\n",
        "result=[]\n",
        "for k in range(len(p)):\n",
        "    #print(k,p[k])\n",
        "    result.append([k,int(p[k])])\n",
        "submit=pd.DataFrame(result)\n",
        "submit.to_csv(\"cat_np_submission.csv\",index=None,header=None)\n"
      ],
      "execution_count": 69,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sbVHogVscN3w",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "BHS4nUn2cN6-",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q9siThVFcN-H",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "E6Nb9JCPcOBM",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "nEKAIov_cOEh",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pNB5iiANcOJP",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}