ensemble_notebook.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Ensembles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Load Requirements"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload\n",
    "\n",
    "import itertools\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from data_utils import get_training, get_testing, HEADER\n",
    "\n",
    "from sklearn.neighbors import KNeighborsClassifier\n",
    "from sklearn.discriminant_analysis import LinearDiscriminantAnalysis\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis\n",
    "from sklearn.ensemble import BaggingClassifier\n",
    "from sklearn.ensemble import AdaBoostClassifier\n",
    "from validation import Validation\n",
    "\n",
    "from sklearn.metrics import confusion_matrix\n",
    "from sklearn import preprocessing\n",
    "from my_pca import my_pca\n",
    "\n",
    "%matplotlib notebook"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bagging ( Logisitic Regression)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "X, y = get_training()\n",
    "val = Validation(X, y, k = 10)\n",
    "\n",
    "# pca, best model\n",
    "base_models = [ (30, LogisticRegression(penalty='l1', C=10)),\n",
    "                (15, KNeighborsClassifier(n_neighbors=3)),\n",
    "                (15, LinearDiscriminantAnalysis()),\n",
    "                (15, QuadraticDiscriminantAnalysis())]\n",
    "\n",
    "base_model_desc = [ 'Logisitic', 'KNN', 'LDA', 'QDA']\n",
    "\n",
    "bagging_results = {\n",
    "    'accuracy' : [],\n",
    "    'recall' : [],\n",
    "    'precision' : []\n",
    "}\n",
    "\n",
    "bsf = (0,-1,3)\n",
    "\n",
    "for i, (comp, model) in enumerate(base_models):\n",
    "    val.update(pca=comp)\n",
    "    mdl = BaggingClassifier(model)\n",
    "    acc = val.cross_val_accuracy(mdl)\n",
    "    r = val.get_detailed_results()\n",
    "    bagging_results['accuracy'].append(np.array(r['accuracy']).mean())\n",
    "    bagging_results['recall'].append(np.array(r['recall']).mean())\n",
    "    bagging_results['precision'].append(np.array(r['precision']).mean())\n",
    "    \n",
    "    if bsf[0] < acc:\n",
    "        bsf = (acc, i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Logisitic\n",
      "0.982778947368\n"
     ]
    }
   ],
   "source": [
    "print base_model_desc[bsf[1]]\n",
    "print bsf[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# plt.figure(figsize=(6, 10))\n",
    "# for i, (name, acc) in enumerate(bagging_results):\n",
    "#     name = base_model_desc[i]\n",
    "#     plt.subplot(len(models), 1, i+1)\n",
    "#     lines = plt.plot(range(1, D+1), acc['accuracy'], 'rd', range(1, D+1),acc['recall'], 'bs', range(1, D+1),acc['precision'], 'g^')\n",
    "#     plt.title('Bagging with different Base Learners')\n",
    "#     plt.xlabel('Model')\n",
    "#     plt.legend(lines, ('accuracy','recall','precision'),loc='lower right')\n",
    "        \n",
    "# plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Bagging Scores"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.close()\n",
    "x = range(1,5)\n",
    "lines = plt.plot(x, bagging_results['accuracy'][0:4], 'rd', x, bagging_results['recall'][0:4], 'bs', x, bagging_results['precision'][0:4], 'g^')\n",
    "plt.legend(lines, ('accuracy','recall','precision'),loc='lower left')\n",
    "plt.title('Bagging with different Base Learners')\n",
    "plt.xticks(x, base_model_desc)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Boosting "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "X, y = get_training()\n",
    "val = Validation(X, y, k = 10, bootstrap = -1)\n",
    "\n",
    "# pca, best model\n",
    "base_models = [ (30, LogisticRegression(penalty='l1', C=10))]\n",
    "\n",
    "base_model_desc = [ 'Logisitic', 'KNN', 'LDA', 'QDA']\n",
    "\n",
    "boost_results = {\n",
    "    'accuracy' : [],\n",
    "    'recall' : [],\n",
    "    'precision' : []\n",
    "}\n",
    "\n",
    "bsf = (0,-1,3)\n",
    "\n",
    "for i, (comp, model) in enumerate(base_models):\n",
    "    val.update(pca=comp)\n",
    "    mdl = AdaBoostClassifier(model, n_estimators=25)\n",
    "    acc = val.cross_val_accuracy(mdl)\n",
    "    r = val.get_detailed_results()\n",
    "    boost_results['accuracy'].append(np.array(r['accuracy']).mean())\n",
    "    boost_results['recall'].append(np.array(r['recall']).mean())\n",
    "    boost_results['precision'].append(np.array(r['precision']).mean())\n",
    "    \n",
    "    if bsf[0] < acc:\n",
    "        bsf = (acc, i)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            if (mpl.ratio != 1) {\n",
       "                fig.send_message(\"set_dpi_ratio\", {'dpi_ratio': mpl.ratio});\n",
       "            }\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var backingStore = this.context.backingStorePixelRatio ||\n",
       "\tthis.context.webkitBackingStorePixelRatio ||\n",
       "\tthis.context.mozBackingStorePixelRatio ||\n",
       "\tthis.context.msBackingStorePixelRatio ||\n",
       "\tthis.context.oBackingStorePixelRatio ||\n",
       "\tthis.context.backingStorePixelRatio || 1;\n",
       "\n",
       "    mpl.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width * mpl.ratio);\n",
       "        canvas.attr('height', height * mpl.ratio);\n",
       "        canvas.attr('style', 'width: ' + width + 'px; height: ' + height + 'px;');\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'] / mpl.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / mpl.ratio;\n",
       "    var x1 = msg['x1'] / mpl.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / mpl.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * mpl.ratio;\n",
       "    var y = canvas_pos.y * mpl.ratio;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    var width = fig.canvas.width/mpl.ratio\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\" width=\"' + width + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width/mpl.ratio\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.close()\n",
    "x = range(1,2)\n",
    "lines = plt.plot(x, boost_results['accuracy'], 'rd', x, boost_results['recall'], 'bs', x, boost_results['precision'], 'g^')\n",
    "plt.legend(lines, ('accuracy','recall','precision'),loc='lower right')\n",
    "plt.title('Boosting with Logisitic')\n",
    "plt.xticks(x, base_model_desc)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Confusion matrices"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def plot_confusion_matrix(cm, classes,\n",
    "                          normalize=False,\n",
    "                          title='Confusion matrix',\n",
    "                          cmap=plt.cm.Blues):\n",
    "    \"\"\"\n",
    "    This function prints and plots the confusion matrix.\n",
    "    Normalization can be applied by setting `normalize=True`.\n",
    "    \"\"\"\n",
    "    plt.imshow(cm, interpolation='nearest', cmap=cmap)\n",
    "    plt.title(title)\n",
    "    plt.colorbar()\n",
    "    tick_marks = np.arange(len(classes))\n",
    "    plt.xticks(tick_marks, classes, rotation=45)\n",
    "    plt.yticks(tick_marks, classes)\n",
    "\n",
    "    if normalize:\n",
    "        cm = cm.astype('float') / cm.sum(axis=1)[:, np.newaxis]\n",
    "        print(\"Normalized confusion matrix\")\n",
    "    else:\n",
    "        print('Confusion matrix, without normalization')\n",
    "\n",
    "    thresh = cm.max() / 2.\n",
    "    for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "        plt.text(j, i, '%.2f'%cm[i, j],\n",
    "                 horizontalalignment=\"center\",\n",
    "                 color=\"white\" if cm[i, j] > thresh else \"black\")\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.gcf().subplots_adjust(bottom=0.2)\n",
    "    plt.ylabel('True label')\n",
    "    plt.xlabel('Predicted label')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# best model\n",
    "X_reduced = my_pca(X,30)\n",
    "base = LogisticRegression(penalty='l1', C=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normalized confusion matrix\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(6,5))\n",
    "mdl = BaggingClassifier(base)\n",
    "y_pred = mdl.fit(X_reduced, y).predict(X_reduced)\n",
    "cm_pca = confusion_matrix(y, y_pred)\n",
    "plot_confusion_matrix(cm_pca, classes=['Benign', 'Malignant'], normalize=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function() {\n",
       "    if (typeof(WebSocket) !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof(MozWebSocket) !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert('Your browser does not have WebSocket support.' +\n",
       "              'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "              'Firefox 4 and 5 are also supported but you ' +\n",
       "              'have to enable WebSockets in about:config.');\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure = function(figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = (this.ws.binaryType != undefined);\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById(\"mpl-warnings\");\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent = (\n",
       "                \"This browser does not support binary websocket messages. \" +\n",
       "                    \"Performance may be slow.\");\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = $('<div/>');\n",
       "    this._root_extra_style(this.root)\n",
       "    this.root.attr('style', 'display: inline-block');\n",
       "\n",
       "    $(parent_element).append(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen =  function () {\n",
       "            fig.send_message(\"supports_binary\", {value: fig.supports_binary});\n",
       "            fig.send_message(\"send_image_mode\", {});\n",
       "            fig.send_message(\"refresh\", {});\n",
       "        }\n",
       "\n",
       "    this.imageObj.onload = function() {\n",
       "            if (fig.image_mode == 'full') {\n",
       "                // Full images could contain transparency (where diff images\n",
       "                // almost always do), so we need to clear the canvas so that\n",
       "                // there is no ghosting.\n",
       "                fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "            }\n",
       "            fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "        };\n",
       "\n",
       "    this.imageObj.onunload = function() {\n",
       "        this.ws.close();\n",
       "    }\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_header = function() {\n",
       "    var titlebar = $(\n",
       "        '<div class=\"ui-dialog-titlebar ui-widget-header ui-corner-all ' +\n",
       "        'ui-helper-clearfix\"/>');\n",
       "    var titletext = $(\n",
       "        '<div class=\"ui-dialog-title\" style=\"width: 100%; ' +\n",
       "        'text-align: center; padding: 3px;\"/>');\n",
       "    titlebar.append(titletext)\n",
       "    this.root.append(titlebar);\n",
       "    this.header = titletext[0];\n",
       "}\n",
       "\n",
       "\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(canvas_div) {\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = $('<div/>');\n",
       "\n",
       "    canvas_div.attr('style', 'position: relative; clear: both; outline: 0');\n",
       "\n",
       "    function canvas_keyboard_event(event) {\n",
       "        return fig.key_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    canvas_div.keydown('key_press', canvas_keyboard_event);\n",
       "    canvas_div.keyup('key_release', canvas_keyboard_event);\n",
       "    this.canvas_div = canvas_div\n",
       "    this._canvas_extra_style(canvas_div)\n",
       "    this.root.append(canvas_div);\n",
       "\n",
       "    var canvas = $('<canvas/>');\n",
       "    canvas.addClass('mpl-canvas');\n",
       "    canvas.attr('style', \"left: 0; top: 0; z-index: 0; outline: 0\")\n",
       "\n",
       "    this.canvas = canvas[0];\n",
       "    this.context = canvas[0].getContext(\"2d\");\n",
       "\n",
       "    var rubberband = $('<canvas/>');\n",
       "    rubberband.attr('style', \"position: absolute; left: 0; top: 0; z-index: 1;\")\n",
       "\n",
       "    var pass_mouse_events = true;\n",
       "\n",
       "    canvas_div.resizable({\n",
       "        start: function(event, ui) {\n",
       "            pass_mouse_events = false;\n",
       "        },\n",
       "        resize: function(event, ui) {\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "        stop: function(event, ui) {\n",
       "            pass_mouse_events = true;\n",
       "            fig.request_resize(ui.size.width, ui.size.height);\n",
       "        },\n",
       "    });\n",
       "\n",
       "    function mouse_event_fn(event) {\n",
       "        if (pass_mouse_events)\n",
       "            return fig.mouse_event(event, event['data']);\n",
       "    }\n",
       "\n",
       "    rubberband.mousedown('button_press', mouse_event_fn);\n",
       "    rubberband.mouseup('button_release', mouse_event_fn);\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband.mousemove('motion_notify', mouse_event_fn);\n",
       "\n",
       "    rubberband.mouseenter('figure_enter', mouse_event_fn);\n",
       "    rubberband.mouseleave('figure_leave', mouse_event_fn);\n",
       "\n",
       "    canvas_div.on(\"wheel\", function (event) {\n",
       "        event = event.originalEvent;\n",
       "        event['data'] = 'scroll'\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        mouse_event_fn(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.append(canvas);\n",
       "    canvas_div.append(rubberband);\n",
       "\n",
       "    this.rubberband = rubberband;\n",
       "    this.rubberband_canvas = rubberband[0];\n",
       "    this.rubberband_context = rubberband[0].getContext(\"2d\");\n",
       "    this.rubberband_context.strokeStyle = \"#000000\";\n",
       "\n",
       "    this._resize_canvas = function(width, height) {\n",
       "        // Keep the size of the canvas, canvas container, and rubber band\n",
       "        // canvas in synch.\n",
       "        canvas_div.css('width', width)\n",
       "        canvas_div.css('height', height)\n",
       "\n",
       "        canvas.attr('width', width);\n",
       "        canvas.attr('height', height);\n",
       "\n",
       "        rubberband.attr('width', width);\n",
       "        rubberband.attr('height', height);\n",
       "    }\n",
       "\n",
       "    // Set the figure to an initial 600x600px, this will subsequently be updated\n",
       "    // upon first draw.\n",
       "    this._resize_canvas(600, 600);\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    $(this.rubberband_canvas).bind(\"contextmenu\",function(e){\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus () {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            // put a spacer in here.\n",
       "            continue;\n",
       "        }\n",
       "        var button = $('<button/>');\n",
       "        button.addClass('ui-button ui-widget ui-state-default ui-corner-all ' +\n",
       "                        'ui-button-icon-only');\n",
       "        button.attr('role', 'button');\n",
       "        button.attr('aria-disabled', 'false');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "\n",
       "        var icon_img = $('<span/>');\n",
       "        icon_img.addClass('ui-button-icon-primary ui-icon');\n",
       "        icon_img.addClass(image);\n",
       "        icon_img.addClass('ui-corner-all');\n",
       "\n",
       "        var tooltip_span = $('<span/>');\n",
       "        tooltip_span.addClass('ui-button-text');\n",
       "        tooltip_span.html(tooltip);\n",
       "\n",
       "        button.append(icon_img);\n",
       "        button.append(tooltip_span);\n",
       "\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    var fmt_picker_span = $('<span/>');\n",
       "\n",
       "    var fmt_picker = $('<select/>');\n",
       "    fmt_picker.addClass('mpl-toolbar-option ui-widget ui-widget-content');\n",
       "    fmt_picker_span.append(fmt_picker);\n",
       "    nav_element.append(fmt_picker_span);\n",
       "    this.format_dropdown = fmt_picker[0];\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = $(\n",
       "            '<option/>', {selected: fmt === mpl.default_extension}).html(fmt);\n",
       "        fmt_picker.append(option)\n",
       "    }\n",
       "\n",
       "    // Add hover states to the ui-buttons\n",
       "    $( \".ui-button\" ).hover(\n",
       "        function() { $(this).addClass(\"ui-state-hover\");},\n",
       "        function() { $(this).removeClass(\"ui-state-hover\");}\n",
       "    );\n",
       "\n",
       "    var status_bar = $('<span class=\"mpl-message\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.request_resize = function(x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', {'width': x_pixels, 'height': y_pixels});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_message = function(type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function() {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({type: \"draw\", figure_id: this.id}));\n",
       "    }\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function(fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] != fig.canvas.width || size[1] != fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1]);\n",
       "        fig.send_message(\"refresh\", {});\n",
       "    };\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function(fig, msg) {\n",
       "    var x0 = msg['x0'];\n",
       "    var y0 = fig.canvas.height - msg['y0'];\n",
       "    var x1 = msg['x1'];\n",
       "    var y1 = fig.canvas.height - msg['y1'];\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0, 0, fig.canvas.width, fig.canvas.height);\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function(fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function(fig, msg) {\n",
       "    var cursor = msg['cursor'];\n",
       "    switch(cursor)\n",
       "    {\n",
       "    case 0:\n",
       "        cursor = 'pointer';\n",
       "        break;\n",
       "    case 1:\n",
       "        cursor = 'default';\n",
       "        break;\n",
       "    case 2:\n",
       "        cursor = 'crosshair';\n",
       "        break;\n",
       "    case 3:\n",
       "        cursor = 'move';\n",
       "        break;\n",
       "    }\n",
       "    fig.rubberband_canvas.style.cursor = cursor;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_message = function(fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function(fig, msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function(fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message(\"ack\", {});\n",
       "}\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function(fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            /* FIXME: We get \"Resource interpreted as Image but\n",
       "             * transferred with MIME type text/plain:\" errors on\n",
       "             * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "             * to be part of the websocket stream */\n",
       "            evt.data.type = \"image/png\";\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src);\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                evt.data);\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "        else if (typeof evt.data === 'string' && evt.data.slice(0, 21) == \"data:image/png;base64\") {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig[\"handle_\" + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\"No handler for the '\" + msg_type + \"' message type: \", msg);\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\"Exception inside the 'handler_\" + msg_type + \"' callback:\", e, e.stack, msg);\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "}\n",
       "\n",
       "// from http://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function(e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e)\n",
       "        e = window.event;\n",
       "    if (e.target)\n",
       "        targ = e.target;\n",
       "    else if (e.srcElement)\n",
       "        targ = e.srcElement;\n",
       "    if (targ.nodeType == 3) // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "\n",
       "    // jQuery normalizes the pageX and pageY\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    // offset() returns the position of the element relative to the document\n",
       "    var x = e.pageX - $(targ).offset().left;\n",
       "    var y = e.pageY - $(targ).offset().top;\n",
       "\n",
       "    return {\"x\": x, \"y\": y};\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * http://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys (original) {\n",
       "  return Object.keys(original).reduce(function (obj, key) {\n",
       "    if (typeof original[key] !== 'object')\n",
       "        obj[key] = original[key]\n",
       "    return obj;\n",
       "  }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function(event, name) {\n",
       "    var canvas_pos = mpl.findpos(event)\n",
       "\n",
       "    if (name === 'button_press')\n",
       "    {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x;\n",
       "    var y = canvas_pos.y;\n",
       "\n",
       "    this.send_message(name, {x: x, y: y, button: event.button,\n",
       "                             step: event.step,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.key_event = function(event, name) {\n",
       "\n",
       "    // Prevent repeat events\n",
       "    if (name == 'key_press')\n",
       "    {\n",
       "        if (event.which === this._key)\n",
       "            return;\n",
       "        else\n",
       "            this._key = event.which;\n",
       "    }\n",
       "    if (name == 'key_release')\n",
       "        this._key = null;\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.which != 17)\n",
       "        value += \"ctrl+\";\n",
       "    if (event.altKey && event.which != 18)\n",
       "        value += \"alt+\";\n",
       "    if (event.shiftKey && event.which != 16)\n",
       "        value += \"shift+\";\n",
       "\n",
       "    value += 'k';\n",
       "    value += event.which.toString();\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, {key: value,\n",
       "                             guiEvent: simpleKeys(event)});\n",
       "    return false;\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function(name) {\n",
       "    if (name == 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message(\"toolbar_button\", {name: name});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function(tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to  previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Pan axes with left mouse, zoom with right\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";var comm_websocket_adapter = function(comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.close = function() {\n",
       "        comm.close()\n",
       "    };\n",
       "    ws.send = function(m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function(msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        // Pass the mpl event to the overriden (by mpl) onmessage function.\n",
       "        ws.onmessage(msg['content']['data'])\n",
       "    });\n",
       "    return ws;\n",
       "}\n",
       "\n",
       "mpl.mpl_figure_comm = function(comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = $(\"#\" + id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm)\n",
       "\n",
       "    function ondownload(figure, format) {\n",
       "        window.open(figure.imageObj.src);\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy,\n",
       "                           ondownload,\n",
       "                           element.get(0));\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element.get(0);\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error(\"Failed to find cell for figure\", id, fig);\n",
       "        return;\n",
       "    }\n",
       "\n",
       "    var output_index = fig.cell_info[2]\n",
       "    var cell = fig.cell_info[0];\n",
       "\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function(fig, msg) {\n",
       "    fig.root.unbind('remove')\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable()\n",
       "    $(fig.parent_element).html('<img src=\"' + dataURL + '\">');\n",
       "    fig.close_ws(fig, msg);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.close_ws = function(fig, msg){\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function(remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] = '<img src=\"' + dataURL + '\">';\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function() {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message(\"ack\", {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () { fig.push_to_output() }, 1000);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function() {\n",
       "    var fig = this;\n",
       "\n",
       "    var nav_element = $('<div/>')\n",
       "    nav_element.attr('style', 'width: 100%');\n",
       "    this.root.append(nav_element);\n",
       "\n",
       "    // Define a callback function for later on.\n",
       "    function toolbar_event(event) {\n",
       "        return fig.toolbar_button_onclick(event['data']);\n",
       "    }\n",
       "    function toolbar_mouse_event(event) {\n",
       "        return fig.toolbar_button_onmouseover(event['data']);\n",
       "    }\n",
       "\n",
       "    for(var toolbar_ind in mpl.toolbar_items){\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) { continue; };\n",
       "\n",
       "        var button = $('<button class=\"btn btn-default\" href=\"#\" title=\"' + name + '\"><i class=\"fa ' + image + ' fa-lg\"></i></button>');\n",
       "        button.click(method_name, toolbar_event);\n",
       "        button.mouseover(tooltip, toolbar_mouse_event);\n",
       "        nav_element.append(button);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = $('<span class=\"mpl-message\" style=\"text-align:right; float: right;\"/>');\n",
       "    nav_element.append(status_bar);\n",
       "    this.message = status_bar[0];\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = $('<div class=\"btn-group inline pull-right\"></div>');\n",
       "    var button = $('<button class=\"btn btn-mini btn-primary\" href=\"#\" title=\"Stop Interaction\"><i class=\"fa fa-power-off icon-remove icon-large\"></i></button>');\n",
       "    button.click(function (evt) { fig.handle_close(fig, {}); } );\n",
       "    button.mouseover('Stop Interaction', toolbar_mouse_event);\n",
       "    buttongrp.append(button);\n",
       "    var titlebar = this.root.find($('.ui-dialog-titlebar'));\n",
       "    titlebar.prepend(buttongrp);\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function(el){\n",
       "    var fig = this\n",
       "    el.on(\"remove\", function(){\n",
       "\tfig.close_ws(fig, {});\n",
       "    });\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function(el){\n",
       "    // this is important to make the div 'focusable\n",
       "    el.attr('tabindex', 0)\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    }\n",
       "    else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "\n",
       "}\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function(event, name) {\n",
       "    var manager = IPython.notebook.keyboard_manager;\n",
       "    if (!manager)\n",
       "        manager = IPython.keyboard_manager;\n",
       "\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which == 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.handle_save = function(fig, msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "}\n",
       "\n",
       "\n",
       "mpl.find_output_cell = function(html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i=0; i<ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code'){\n",
       "            for (var j=0; j<cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] == html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "}\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel != null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target('matplotlib', mpl.mpl_figure_comm);\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Normalized confusion matrix\n"
     ]
    }
   ],
   "source": [
    "plt.figure(figsize=(6,5))\n",
    "mdl = AdaBoostClassifier(base)\n",
    "y_pred = mdl.fit(X_reduced, y).predict(X_reduced)\n",
    "cm_pca = confusion_matrix(y, y_pred)\n",
    "plot_confusion_matrix(cm_pca, classes=['Benign', 'Malignant'], normalize=True)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}