src/HiringBias.ipynb

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      "source": [
        "<a href=\"https://colab.research.google.com/github/maciejskorski/ml_examples/blob/master/HiringBias.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "![Colab](https://img.shields.io/badge/Google-Colab-F9AB00?style=plain&logo=googlecolab&color=525252)\n",
        "[![scikit-learn](https://img.shields.io/badge/scikit--learn-%23F7931E.svg?style=plain&logo=scikit-learn&logoColor=white)](https://scikit-learn.org/stable/)\n",
        "[![Matplotlib](https://img.shields.io/badge/Matplotlib-%23ffffff.svg?style=plain&logo=Matplotlib&logoColor=black)](https://matplotlib.org/)\n",
        "[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)\n",
        "\n",
        "# Hiring Bias\n",
        "\n",
        "Is gender bias in hiring easy to judge? This study, on synthetic data, demonstrates that such questions require carefull statistical modelling."
      ],
      "metadata": {
        "id": "YYNkCHYGkBmv"
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      "source": [
        "## Data\n",
        "\n",
        "Read two data sources: admissions and candidate tables, and merge them."
      ],
      "metadata": {
        "id": "zrfckMJTojAf"
      }
    },
    {
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      "source": [
        "from google.colab import files\n",
        "import pandas as pd\n",
        "\n",
        "uploaded = files.upload()\n",
        "!unzip -d data hiring_datasets.zip\n",
        "\n",
        "df_admisions = pd.read_csv(\"/content/data/admissions.csv\")\n",
        "df_candidates = pd.read_csv(\"/content/data/candidates.csv\")\n",
        "\n",
        "# NOTE: remove duplicates and check 1:1 match on the tables\n",
        "df_candidates.set_index(\"candidate_id\", inplace=True)\n",
        "assert df_candidates.index.is_unique\n",
        "df_admisions.drop_duplicates(inplace=True)\n",
        "df_admisions.set_index(\"candidate_id\", inplace=True)\n",
        "assert df_admisions.index.is_unique\n",
        "\n",
        "df = df_candidates.join(df_admisions)\n",
        "assert len(df_candidates) == len(df_admisions)\n",
        "df.head()\n",
        "print(df.shape)"
      ],
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              "//\n",
              "//      http://www.apache.org/licenses/LICENSE-2.0\n",
              "//\n",
              "// Unless required by applicable law or agreed to in writing, software\n",
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              "// See the License for the specific language governing permissions and\n",
              "// limitations under the License.\n",
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      "cell_type": "markdown",
      "source": [
        "## Exploratory Analysis\n",
        "\n",
        "The data coverage looks good: the missing data is mostly card id (about 2/3 missing) which is hopefully not valuable. \n",
        "\n",
        "The plots illustrate the impact of predictors (age, gender, family size, department) on the admission status. Some quick findings are:\n",
        "* older candidates are more likely to get hired\n",
        "* females are rejected more often compared to males - we will see that this alone is not enough to claim discrimination (!)\n",
        "* competetitive departments - such as F - seem to overly reject, when compared to others (Data Science roles? :D)\n",
        "* applicants without children are rarely accepted\n",
        "\n",
        "NOTE: The data summarization statistics revealed one record with anomalous age (removed).\n"
      ],
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        "id": "n-bxu7Nto0on"
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        "df.isna().mean()"
      ],
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           0.000000\n",
              "age            0.000000\n",
              "gender         0.000000\n",
              "no_children    0.147572\n",
              "emp_card_id    0.650062\n",
              "department     0.000000\n",
              "admit          0.000000\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns\n",
        "\n",
        "plt.style.use(\"ggplot\")\n",
        "hue_order = [\"Admitted\", \"Rejected\"]\n",
        "\n",
        "fig, axs = plt.subplots(2, 2, figsize=(12, 6))\n",
        "axs = axs.ravel()\n",
        "\n",
        "# analyze age impact on hiring\n",
        "ax = axs[0]\n",
        "df = df[df[\"age\"] <= 100]\n",
        "sns.kdeplot(\n",
        "    data=df,\n",
        "    x=\"age\",\n",
        "    hue=\"admit\",\n",
        "    common_norm=False,\n",
        "    clip=(0, 100),\n",
        "    ax=ax,\n",
        "    hue_order=hue_order,\n",
        ")\n",
        "ax.set_title(f'Admisions vs age (mean age={df[\"age\"].mean().round(2)}).')\n",
        "\n",
        "# analyze deparment impact on hiring\n",
        "ax = axs[1]\n",
        "df_department_agg = df.groupby(\"department\").value_counts([\"admit\"])\n",
        "df_department_agg.name = \"count\"\n",
        "sns.barplot(\n",
        "    data=df_department_agg.reset_index(),\n",
        "    y=\"count\",\n",
        "    x=\"department\",\n",
        "    hue=\"admit\",\n",
        "    ax=ax,\n",
        "    hue_order=hue_order,\n",
        ")\n",
        "ax.set_title(f\"Admisions vs departament.\")\n",
        "\n",
        "# analyze gender impact on hiring\n",
        "ax = axs[2]\n",
        "df_sex_agg = df.groupby(\"gender\").value_counts([\"admit\"])\n",
        "df_sex_agg.name = \"count\"\n",
        "sns.barplot(\n",
        "    data=df_sex_agg.reset_index(),\n",
        "    y=\"count\",\n",
        "    x=\"gender\",\n",
        "    hue=\"admit\",\n",
        "    ax=ax,\n",
        "    hue_order=hue_order,\n",
        ")\n",
        "ax.set_title(f\"Admisions vs gender.\")\n",
        "\n",
        "# analyze family impact on hiring\n",
        "ax = axs[3]\n",
        "df_family_agg = df.groupby(\"no_children\").value_counts([\"admit\"])\n",
        "df_family_agg.name = \"count\"\n",
        "sns.barplot(\n",
        "    data=df_family_agg.reset_index(),\n",
        "    y=\"count\",\n",
        "    x=\"no_children\",\n",
        "    hue=\"admit\",\n",
        "    ax=ax,\n",
        "    hue_order=hue_order,\n",
        ")\n",
        "ax.set_title(f\"Admisions vs no_children.\")\n",
        "\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
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          "data": {
            "text/plain": [
              "<Figure size 1200x600 with 4 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_family_agg"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7j4clcRYmUGr",
        "outputId": "2c17bb7f-c434-4403-eb7e-d9648251a76c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "no_children  admit   \n",
              "0.0          Rejected    13355\n",
              "             Admitted      761\n",
              "1.0          Admitted     6959\n",
              "             Rejected     6483\n",
              "2.0          Admitted     6969\n",
              "             Rejected     6473\n",
              "3.0          Admitted      747\n",
              "             Rejected      679\n",
              "4.0          Admitted        8\n",
              "             Rejected        4\n",
              "Name: count, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Predictive Modelling\n",
        "\n",
        "We will build a simple predicitve model of reasonable accuracy, and use it to quantitatively confirm the findings from the exploratory analysis."
      ],
      "metadata": {
        "id": "2v_i23XKxE5i"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model\n",
        "\n",
        "The model uses `sklearn.pipeline` to combine an imputer, feature scaler and a one-layer linear classifier to predict \"admitted\" outcome.\n",
        "\n",
        "Categorical features such as the number of children and department id are one-hot encoded in `pandas`. "
      ],
      "metadata": {
        "id": "DsRfylCXA1te"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "X_enc = pd.concat(\n",
        "    [\n",
        "        df[[\"age\"]],\n",
        "        pd.get_dummies(df[\"no_children\"], prefix=\"kids\", drop_first=False),\n",
        "        pd.get_dummies(df[\"gender\"], prefix=\"sex\", drop_first=True),\n",
        "        pd.get_dummies(df[\"department\"], prefix=\"department\", drop_first=False),\n",
        "    ],\n",
        "    axis=1,\n",
        ")\n",
        "y_enc = df[\"admit\"] == \"Admitted\"\n",
        "\n",
        "X = X_enc.to_numpy().astype(\"float32\")\n",
        "y = y_enc.to_numpy().ravel().astype(\"float32\")\n",
        "\n",
        "X_enc.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 238
        },
        "id": "a6mNi3mtsCO4",
        "outputId": "643bdcac-3098-4c06-8fb1-41777ef4a388"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "               age  kids_0.0  kids_1.0  kids_2.0  kids_3.0  kids_4.0  \\\n",
              "candidate_id                                                           \n",
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              "              sex_Male  department_A  department_B  department_C  \\\n",
              "candidate_id                                                       \n",
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              "candidate_id                                            \n",
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          },
          "metadata": {},
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        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df.isna().mean()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EDpXhrR3ewDF",
        "outputId": "3897da9b-6d94-4b13-ff08-16c97a49d358"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "name           0.000000\n",
              "age            0.000000\n",
              "gender         0.000000\n",
              "no_children    0.147575\n",
              "emp_card_id    0.650075\n",
              "department     0.000000\n",
              "admit          0.000000\n",
              "dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import sklearn\n",
        "from sklearn.preprocessing import StandardScaler\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.impute import SimpleImputer\n",
        "from sklearn.dummy import DummyClassifier\n",
        "\n",
        "\n",
        "model = Pipeline(\n",
        "    [\n",
        "        (\"imputer\", SimpleImputer()),\n",
        "        (\"scaler\", StandardScaler()),\n",
        "        (\"classifier\", LogisticRegression()),\n",
        "    ]\n",
        ")\n",
        "\n",
        "baseline_model = Pipeline(\n",
        "    [\n",
        "        (\"imputer\", SimpleImputer()),\n",
        "        (\"scaler\", StandardScaler()),\n",
        "        (\"classifier\", DummyClassifier(strategy=\"most_frequent\")),\n",
        "    ]\n",
        ")"
      ],
      "metadata": {
        "id": "9gOrs6axzlwU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Validation\n",
        "\n",
        "Since the problem is not unbalanced, it makes sense to look at the good old accuracy. Furthermore, we will evaluate the ROC curve of this binary classificaiton. For both methodological robustness and coding brevity, we will use cross-validation provided by the `sklearn` API. Note that with recent releases of `sklearn` it is convenient to use `RocCurveDisplay` to quickly visualize ROC curves.\n",
        "\n",
        "The model is quite good and significantly outperforms the \"most frequent guess\" baseline."
      ],
      "metadata": {
        "id": "3r-Sf3_LCD_v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import StratifiedKFold\n",
        "from sklearn.model_selection import cross_val_score\n",
        "from sklearn.metrics import roc_auc_score\n",
        "from sklearn.metrics import make_scorer\n",
        "\n",
        "rocauc_scorer = make_scorer(roc_auc_score)\n",
        "\n",
        "cv = StratifiedKFold(n_splits=10, shuffle=True)\n",
        "scores = cross_val_score(model, X, y, cv=cv)\n",
        "benchmark_scores = cross_val_score(baseline_model, X, y, cv=cv)\n",
        "print(\"Model accuracy: {:.3f}±{:.3f}\".format(scores.mean(), scores.std()))\n",
        "print(\n",
        "    \"Majority-guess (baseline) accuracy: {:.3f}±{:.3f}\".format(\n",
        "        benchmark_scores.mean(), benchmark_scores.std()\n",
        "    )\n",
        ")\n",
        "rocauc_scores = cross_val_score(model, X, y, cv=cv, scoring=rocauc_scorer)\n",
        "print(\"Model ROC-AUC: {:.3f}±{:.3f}\".format(rocauc_scores.mean(), rocauc_scores.std()))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-1pSqzTs4DrV",
        "outputId": "ed279645-dd50-46fd-eeab-c25ee4ca7cfc"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model accuracy: 0.897±0.003\n",
            "Majority-guess (baseline) accuracy: 0.612±0.000\n",
            "Model ROC-AUC: 0.893±0.005\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "from scipy import interp\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn import svm, datasets\n",
        "from sklearn.metrics import roc_curve, auc, RocCurveDisplay\n",
        "\n",
        "\n",
        "ax = plt.gca()\n",
        "for i, (train_idx, test_idx) in enumerate(cv.split(X, y)):\n",
        "    model.fit(X[train_idx], y[train_idx]).predict_proba(X[test_idx])\n",
        "    display = RocCurveDisplay.from_estimator(\n",
        "        model, X[test_idx], y[test_idx], ax=ax, pos_label=1, name=f\"fold={i}\"\n",
        "    )\n",
        "\n",
        "plt.plot([0, 1], [0, 1], \"--\", color=(0.6, 0.6, 0.6), label=\"Random Guess\")\n",
        "plt.xlabel(\"False Positive Rate\")\n",
        "plt.ylabel(\"True Positive Rate\")\n",
        "plt.title(\"ROC for predicting admission\")\n",
        "plt.legend(loc=\"lower right\")\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 477
        },
        "id": "vYx9PkQBFWvO",
        "outputId": "4a4824b6-d413-4789-ba5f-b9dd1034088a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 640x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Interpretation / Statistical Insights\n",
        "\n",
        "Cherry on the pie: we will look into statistical insights. \n",
        "\n",
        "Firstly, we will plot model weights as proxies for feature importances. Secondly, we will apply bootstrapping to confirm significance statistically. \n",
        "\n",
        "**Concusion**: *Age has the strongest positive impact* on the hiring decision, followed by *having children*, and *department competetiveness* is important too. \n",
        "When accounting for age and children we see no  evidence for discrimination towards females anymore. Males in this dataset have much different work-family profiles than females: they tend to have higher age and have more family obligations (both thought as proxies for experience and loyalty) and apply for less competetive roles (cf. departments A vs C)."
      ],
      "metadata": {
        "id": "txu_hjqoDstr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "fig, axs = plt.subplots(1, 2, figsize=(12, 4))\n",
        "\n",
        "# compute and visualize feature importances\n",
        "\n",
        "ax = axs[0]\n",
        "model.fit(X, y)\n",
        "importances = pd.Series(\n",
        "    dict(zip(X_enc.columns, *model.named_steps[\"classifier\"].coef_))\n",
        ")\n",
        "importances = importances.sort_values(key=lambda x: abs(x), ascending=True)\n",
        "fig = importances.plot(kind=\"barh\", ax=ax)\n",
        "ax.set_title(\"Predictors importance (by model weights)\")\n",
        "\n",
        "# bootstrap and visualize distributon of importances\n",
        "\n",
        "from sklearn.utils.random import sample_without_replacement\n",
        "\n",
        "N_BOOTSTRAPS = 1000\n",
        "\n",
        "model_coefs = []\n",
        "\n",
        "for _ in range(N_BOOTSTRAPS):\n",
        "    train_idx = sample_without_replacement(len(X), 1000)\n",
        "    model.fit(X[train_idx], y[train_idx])\n",
        "    model_coefs.append(model.named_steps[\"classifier\"].coef_.ravel())\n",
        "\n",
        "model_coefs = np.array(model_coefs)\n",
        "\n",
        "ax = axs[1]\n",
        "importances = pd.DataFrame(model_coefs, columns=X_enc.columns)\n",
        "sns.histplot(data=importances, common_norm=False, kde=True, ax=ax)\n",
        "ax.set_title(\"Feature importances (model weights, bootstrapped)\")\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 392
        },
        "id": "R8DJwP9r6Rp7",
        "outputId": "345e2cc0-6d44-47fa-9c9d-baf52fd7a0a3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x400 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# differences in males / females\n",
        "\n",
        "pd.concat(\n",
        "    [\n",
        "        df.groupby(\"gender\").agg(\n",
        "            {\n",
        "                \"age\": \"mean\",\n",
        "                \"no_children\": \"mean\",\n",
        "            }\n",
        "        ),\n",
        "        df.groupby(\"gender\")[\"department\"].value_counts(normalize=True).unstack(),\n",
        "    ],\n",
        "    axis=1,\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 143
        },
        "id": "iJKFE3aof4Pk",
        "outputId": "69146b1d-cf9a-46d7-d81b-fd2e36f8d7ba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              age  no_children         A         B         C         D  \\\n",
              "gender                                                                   \n",
              "Female  32.529205     0.480501  0.058856  0.013624  0.323161  0.204360   \n",
              "Male    43.945777     1.501136  0.306554  0.208108  0.120777  0.154966   \n",
              "\n",
              "               E         F  \n",
              "gender                      \n",
              "Female  0.214169  0.185831  \n",
              "Male    0.070980  0.138615  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-270c687d-c7c6-4a09-8208-6535dfcc14b7\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>age</th>\n",
              "      <th>no_children</th>\n",
              "      <th>A</th>\n",
              "      <th>B</th>\n",
              "      <th>C</th>\n",
              "      <th>D</th>\n",
              "      <th>E</th>\n",
              "      <th>F</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>gender</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Female</th>\n",
              "      <td>32.529205</td>\n",
              "      <td>0.480501</td>\n",
              "      <td>0.058856</td>\n",
              "      <td>0.013624</td>\n",
              "      <td>0.323161</td>\n",
              "      <td>0.204360</td>\n",
              "      <td>0.214169</td>\n",
              "      <td>0.185831</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Male</th>\n",
              "      <td>43.945777</td>\n",
              "      <td>1.501136</td>\n",
              "      <td>0.306554</td>\n",
              "      <td>0.208108</td>\n",
              "      <td>0.120777</td>\n",
              "      <td>0.154966</td>\n",
              "      <td>0.070980</td>\n",
              "      <td>0.138615</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-270c687d-c7c6-4a09-8208-6535dfcc14b7')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "      \n",
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              "      display:flex;\n",
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              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
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              "      fill: #174EA6;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
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              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-270c687d-c7c6-4a09-8208-6535dfcc14b7 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-270c687d-c7c6-4a09-8208-6535dfcc14b7');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount(\"/content/drive\")\n",
        "!pip install black[jupyter] --quiet\n",
        "!black /content/drive/MyDrive/'Colab Notebooks'/'HiringBias.ipynb'"
      ],
      "metadata": {
        "id": "5T09rsiLxH5a",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ecd1fd43-e1e4-496a-a2db-7e05d2c3cf2c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",
            "\u001b[1mAll done! ✨ 🍰 ✨\u001b[0m\n",
            "\u001b[34m1 file \u001b[0mleft unchanged.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# More\n",
        "\n",
        "In terms of model improvements, feature selection did not make sense on data of that small-dimension. One can always engineer more features or bring an even more powerful model. Perhaps insights can be easier delivered and nicer demonstrated with explainable techniques, such as Shapley values. However, while building the model is easy, optimization is much harder and time-consuming. This notebook aims to demonstrate quick and robust fiindings, particularly matching conclusions of exploratory analysis and statistical inference."
      ],
      "metadata": {
        "id": "2r4b0LcyD1kp"
      }
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "uqUjJlYvnU4h"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}