{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["# 2A.data - Classification, r\u00e9gression, anomalies - correction\n", "\n", "Le jeu de donn\u00e9es [Wine Quality Data Set](https://archive.ics.uci.edu/ml/datasets/Wine+Quality) contient 5000 vins d\u00e9crits par leurs caract\u00e9ristiques chimiques et \u00e9valu\u00e9s par un expert. Peut-on s'approcher de l'expert \u00e0 l'aide d'un mod\u00e8le de machine learning."]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["%matplotlib inline\n", "import matplotlib.pyplot as plt"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [{"data": {"text/html": ["
\n", ""], "text/plain": [""]}, "execution_count": 3, "metadata": {}, "output_type": "execute_result"}], "source": ["from jyquickhelper import add_notebook_menu\n", "add_notebook_menu()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Les donn\u00e9es\n", "\n", "On peut les r\u00e9cup\u00e9rer sur [github...data_2a](https://github.com/sdpython/ensae_teaching_cs/tree/master/src/ensae_teaching_cs/data/data_1a)."]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " fixed_acidity \n", " volatile_acidity \n", " citric_acid \n", " residual_sugar \n", " chlorides \n", " free_sulfur_dioxide \n", " total_sulfur_dioxide \n", " density \n", " pH \n", " sulphates \n", " alcohol \n", " quality \n", " color \n", " \n", " \n", " \n", " \n", " 0 \n", " 7.4 \n", " 0.70 \n", " 0.00 \n", " 1.9 \n", " 0.076 \n", " 11.0 \n", " 34.0 \n", " 0.9978 \n", " 3.51 \n", " 0.56 \n", " 9.4 \n", " 5 \n", " red \n", " \n", " \n", " 1 \n", " 7.8 \n", " 0.88 \n", " 0.00 \n", " 2.6 \n", " 0.098 \n", " 25.0 \n", " 67.0 \n", " 0.9968 \n", " 3.20 \n", " 0.68 \n", " 9.8 \n", " 5 \n", " red \n", " \n", " \n", " 2 \n", " 7.8 \n", " 0.76 \n", " 0.04 \n", " 2.3 \n", " 0.092 \n", " 15.0 \n", " 54.0 \n", " 0.9970 \n", " 3.26 \n", " 0.65 \n", " 9.8 \n", " 5 \n", " red \n", " \n", " \n", " 3 \n", " 11.2 \n", " 0.28 \n", " 0.56 \n", " 1.9 \n", " 0.075 \n", " 17.0 \n", " 60.0 \n", " 0.9980 \n", " 3.16 \n", " 0.58 \n", " 9.8 \n", " 6 \n", " red \n", " \n", " \n", " 4 \n", " 7.4 \n", " 0.70 \n", " 0.00 \n", " 1.9 \n", " 0.076 \n", " 11.0 \n", " 34.0 \n", " 0.9978 \n", " 3.51 \n", " 0.56 \n", " 9.4 \n", " 5 \n", " red \n", " \n", " \n", "
\n", "
"], "text/plain": [" fixed_acidity volatile_acidity citric_acid residual_sugar chlorides \\\n", "0 7.4 0.70 0.00 1.9 0.076 \n", "1 7.8 0.88 0.00 2.6 0.098 \n", "2 7.8 0.76 0.04 2.3 0.092 \n", "3 11.2 0.28 0.56 1.9 0.075 \n", "4 7.4 0.70 0.00 1.9 0.076 \n", "\n", " free_sulfur_dioxide total_sulfur_dioxide density pH sulphates \\\n", "0 11.0 34.0 0.9978 3.51 0.56 \n", "1 25.0 67.0 0.9968 3.20 0.68 \n", "2 15.0 54.0 0.9970 3.26 0.65 \n", "3 17.0 60.0 0.9980 3.16 0.58 \n", "4 11.0 34.0 0.9978 3.51 0.56 \n", "\n", " alcohol quality color \n", "0 9.4 5 red \n", "1 9.8 5 red \n", "2 9.8 5 red \n", "3 9.8 6 red \n", "4 9.4 5 red "]}, "execution_count": 4, "metadata": {}, "output_type": "execute_result"}], "source": ["from ensae_teaching_cs.data import wines_quality\n", "from pandas import read_csv\n", "df = read_csv(wines_quality(local=True, filename=True))\n", "df.head()"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["ax = df['quality'].hist(bins=16)\n", "ax.set_title(\"Distribution des notes\");"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Il y a peu de tr\u00e8s mauvais ou tr\u00e8s bons vins. On d\u00e9coupe en apprentissage / test ce qui va n\u00e9cessairement rendre leur pr\u00e9diction complexe : un mod\u00e8le reproduit en quelque sorte ce qu'il voit."]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"text/plain": ["((3248, 12), (3249, 12))"]}, "execution_count": 6, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.model_selection import train_test_split\n", "X = df.drop(\"quality\", axis=1)\n", "y = df[\"quality\"]\n", "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.5)\n", "X_train.shape, X_test.shape"]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " ctrain \n", " ctest \n", " ratio \n", " \n", " \n", " color \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " 3 \n", " 12 \n", " 18 \n", " 1.500000 \n", " \n", " \n", " 4 \n", " 94 \n", " 122 \n", " 1.297872 \n", " \n", " \n", " 5 \n", " 1076 \n", " 1062 \n", " 0.986989 \n", " \n", " \n", " 6 \n", " 1429 \n", " 1407 \n", " 0.984605 \n", " \n", " \n", " 7 \n", " 536 \n", " 543 \n", " 1.013060 \n", " \n", " \n", " 8 \n", " 98 \n", " 95 \n", " 0.969388 \n", " \n", " \n", " 9 \n", " 3 \n", " 2 \n", " 0.666667 \n", " \n", " \n", "
\n", "
"], "text/plain": [" ctrain ctest ratio\n", "color \n", "3 12 18 1.500000\n", "4 94 122 1.297872\n", "5 1076 1062 0.986989\n", "6 1429 1407 0.984605\n", "7 536 543 1.013060\n", "8 98 95 0.969388\n", "9 3 2 0.666667"]}, "execution_count": 7, "metadata": {}, "output_type": "execute_result"}], "source": ["from pandas import DataFrame\n", "\n", "def distribution(y_train, y_test):\n", " df_train = DataFrame(dict(color=y_train))\n", " df_test = DataFrame(dict(color=y_test))\n", " df_train['ctrain'] = 1\n", " df_test['ctest'] = 1\n", " h_train = df_train.groupby('color').count()\n", " h_test = df_test.groupby('color').count()\n", " merge = h_train.join(h_test, how='outer')\n", " merge[\"ratio\"] = merge.ctest / merge.ctrain\n", " return merge\n", " \n", "distribution(y_train, y_test)"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["ax = y_train.hist(bins=24, label=\"train\", align=\"right\")\n", "y_test.hist(bins=24, label=\"test\", ax=ax, align=\"left\")\n", "ax.set_title(\"Distribution des notes\")\n", "ax.legend();"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Avec un peu de chance, les notes extr\u00eames sont pr\u00e9sentes dans les bases d'apprentissages et de tests mais une note seule a peu d'influence sur un mod\u00e8le. Pour s'assurer une meilleur r\u00e9partition train / test, on peut s'assurer que chaque note est bien r\u00e9partie de chaque c\u00f4t\u00e9. On se sert du param\u00e8tre [stratify](https://scikit-learn.org/stable/modules/generated/sklearn.model_selection.train_test_split.html)."]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y, test_size=0.5)\n", "X_train.shape, X_test.shape\n", "ax = y_train.hist(bins=24, label=\"train\", align=\"right\")\n", "y_test.hist(bins=24, label=\"test\", ax=ax, align=\"left\")\n", "ax.set_title(\"Distribution des notes - statifi\u00e9e\")\n", "ax.legend();"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " ctrain \n", " ctest \n", " ratio \n", " \n", " \n", " color \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " 3 \n", " 15 \n", " 15 \n", " 1.000000 \n", " \n", " \n", " 4 \n", " 108 \n", " 108 \n", " 1.000000 \n", " \n", " \n", " 5 \n", " 1069 \n", " 1069 \n", " 1.000000 \n", " \n", " \n", " 6 \n", " 1418 \n", " 1418 \n", " 1.000000 \n", " \n", " \n", " 7 \n", " 539 \n", " 540 \n", " 1.001855 \n", " \n", " \n", " 8 \n", " 96 \n", " 97 \n", " 1.010417 \n", " \n", " \n", " 9 \n", " 3 \n", " 2 \n", " 0.666667 \n", " \n", " \n", "
\n", "
"], "text/plain": [" ctrain ctest ratio\n", "color \n", "3 15 15 1.000000\n", "4 108 108 1.000000\n", "5 1069 1069 1.000000\n", "6 1418 1418 1.000000\n", "7 539 540 1.001855\n", "8 96 97 1.010417\n", "9 3 2 0.666667"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["distribution(y_train, y_test)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["La r\u00e9partition des notes selon apprentissage / test est plus uniforme."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Premier mod\u00e8le"]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["could not convert string to float: 'white'\n"]}], "source": ["from sklearn.linear_model import LogisticRegression\n", "logreg = LogisticRegression()\n", "try:\n", " logreg.fit(X_train, y_train)\n", "except Exception as e:\n", " print(e)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Une colonne n'est pas num\u00e9rique. On utilise un [OneHotEncoder](https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.OneHotEncoder.html)."]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"data": {"text/plain": ["<3249x2 sparse matrix of type ''\n", "\twith 3249 stored elements in Compressed Sparse Row format>"]}, "execution_count": 12, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.preprocessing import OneHotEncoder\n", "one = OneHotEncoder()\n", "one.fit(X_train[['color']])\n", "tr = one.transform(X_test[[\"color\"]])\n", "tr"]}, {"cell_type": "markdown", "metadata": {}, "source": ["La matrice est [sparse ou creuse](https://fr.wikipedia.org/wiki/Matrice_creuse)."]}, {"cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [{"data": {"text/plain": ["matrix([[0., 1.],\n", " [0., 1.],\n", " [0., 1.],\n", " [0., 1.],\n", " [0., 1.]])"]}, "execution_count": 13, "metadata": {}, "output_type": "execute_result"}], "source": ["tr.todense()[:5]"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Ensuite il faut fusionner ces deux colonnes avec les donn\u00e9es ou une seule puisqu'elles sont corr\u00e9l\u00e9es. Ou alors on \u00e9crit un pipeline..."]}, {"cell_type": "code", "execution_count": 13, "metadata": {"scrolled": false}, "outputs": [{"data": {"text/plain": ["array([[0.0000e+00, 6.0000e+00, 3.4000e-01, 2.4000e-01, 5.4000e+00,\n", " 6.0000e-02, 2.3000e+01, 1.2600e+02, 9.9510e-01, 3.2500e+00,\n", " 4.4000e-01, 9.0000e+00],\n", " [0.0000e+00, 6.7000e+00, 4.1000e-01, 2.7000e-01, 2.6000e+00,\n", " 3.3000e-02, 2.5000e+01, 8.5000e+01, 9.9086e-01, 3.0500e+00,\n", " 3.4000e-01, 1.1700e+01]])"]}, "execution_count": 14, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.pipeline import Pipeline\n", "from sklearn.compose import ColumnTransformer\n", "\n", "numeric_features = [c for c in X_train if c != 'color']\n", "\n", "pipe = Pipeline([\n", " (\"prep\", ColumnTransformer([\n", " (\"color\", Pipeline([\n", " ('one', OneHotEncoder()),\n", " ('select', ColumnTransformer([('sel1', 'passthrough', [0])]))\n", " ]), ['color']),\n", " (\"others\", \"passthrough\", numeric_features)\n", " ])),\n", "])\n", "\n", "pipe.fit(X_train)\n", "pipe.transform(X_test)[:2]"]}, {"cell_type": "code", "execution_count": 14, "metadata": {"scrolled": false}, "outputs": [{"data": {"text/html": ["\n", ""], "text/plain": [""]}, "execution_count": 15, "metadata": {}, "output_type": "execute_result"}], "source": ["from jyquickhelper import RenderJsDot\n", "from mlinsights.plotting import pipeline2dot\n", "dot = pipeline2dot(pipe, X_train)\n", "RenderJsDot(dot)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Il reste quelques bugs. On ajoute un classifieur."]}, {"cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\sklearn\\linear_model\\_logistic.py:814: ConvergenceWarning: lbfgs failed to converge (status=1):\n", "STOP: TOTAL NO. of ITERATIONS REACHED LIMIT.\n", "\n", "Increase the number of iterations (max_iter) or scale the data as shown in:\n", " https://scikit-learn.org/stable/modules/preprocessing.html\n", "Please also refer to the documentation for alternative solver options:\n", " https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression\n", " n_iter_i = _check_optimize_result(\n"]}, {"data": {"text/plain": ["Pipeline(steps=[('prep',\n", " ColumnTransformer(transformers=[('color',\n", " Pipeline(steps=[('one',\n", " OneHotEncoder()),\n", " ('select',\n", " ColumnTransformer(transformers=[('sel1',\n", " 'passthrough',\n", " [0])]))]),\n", " ['color']),\n", " ('others', 'passthrough',\n", " ['fixed_acidity',\n", " 'volatile_acidity',\n", " 'citric_acid',\n", " 'residual_sugar',\n", " 'chlorides',\n", " 'free_sulfur_dioxide',\n", " 'total_sulfur_dioxide',\n", " 'density', 'pH', 'sulphates',\n", " 'alcohol'])])),\n", " ('lr', LogisticRegression(max_iter=1000))])"]}, "execution_count": 16, "metadata": {}, "output_type": "execute_result"}], "source": ["pipe = Pipeline([\n", " (\"prep\", ColumnTransformer([\n", " (\"color\", Pipeline([\n", " ('one', OneHotEncoder()),\n", " ('select', ColumnTransformer([('sel1', 'passthrough', [0])]))\n", " ]), ['color']),\n", " (\"others\", \"passthrough\", numeric_features)\n", " ])),\n", " (\"lr\", LogisticRegression(max_iter=1000)),\n", "])\n", "\n", "pipe.fit(X_train, y_train)"]}, {"cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": [" precision recall f1-score support\n", "\n", " 3 0.00 0.00 0.00 15\n", " 4 0.00 0.00 0.00 108\n", " 5 0.60 0.61 0.60 1069\n", " 6 0.52 0.72 0.60 1418\n", " 7 0.40 0.14 0.21 540\n", " 8 0.00 0.00 0.00 97\n", " 9 0.00 0.00 0.00 2\n", "\n", " accuracy 0.54 3249\n", " macro avg 0.22 0.21 0.20 3249\n", "weighted avg 0.49 0.54 0.50 3249\n", "\n"]}, {"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "C:\\Python395_x64\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "C:\\Python395_x64\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n"]}], "source": ["from sklearn.metrics import classification_report\n", "print(classification_report(y_test, pipe.predict(X_test)))"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Pas extraordinaire."]}, {"cell_type": "code", "execution_count": 17, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": [" precision recall f1-score support\n", "\n", " 3 0.00 0.00 0.00 15\n", " 4 0.73 0.07 0.13 108\n", " 5 0.70 0.71 0.70 1069\n", " 6 0.62 0.76 0.68 1418\n", " 7 0.65 0.44 0.52 540\n", " 8 0.83 0.30 0.44 97\n", " 9 0.00 0.00 0.00 2\n", "\n", " accuracy 0.65 3249\n", " macro avg 0.50 0.33 0.35 3249\n", "weighted avg 0.66 0.65 0.63 3249\n", "\n"]}, {"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "C:\\Python395_x64\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n", "C:\\Python395_x64\\lib\\site-packages\\sklearn\\metrics\\_classification.py:1318: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n", " _warn_prf(average, modifier, msg_start, len(result))\n"]}], "source": ["from sklearn.ensemble import RandomForestClassifier\n", "\n", "pipe = Pipeline([\n", " (\"prep\", ColumnTransformer([\n", " (\"color\", Pipeline([\n", " ('one', OneHotEncoder()),\n", " ('select', ColumnTransformer([('sel1', 'passthrough', [0])]))\n", " ]), ['color']),\n", " (\"others\", \"passthrough\", numeric_features)\n", " ])),\n", " (\"lr\", RandomForestClassifier()),\n", "])\n", "\n", "pipe.fit(X_train, y_train)\n", "print(classification_report(y_test, pipe.predict(X_test)))"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Beaucoup mieux."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Courbe ROC pour chaque classe"]}, {"cell_type": "code", "execution_count": 18, "metadata": {}, "outputs": [], "source": ["from sklearn.metrics import roc_curve, auc\n", "\n", "labels = pipe.steps[1][1].classes_\n", "y_score = pipe.predict_proba(X_test)\n", "\n", "fpr = dict()\n", "tpr = dict()\n", "roc_auc = dict()\n", "for i, cl in enumerate(labels):\n", " fpr[cl], tpr[cl], _ = roc_curve(y_test == cl, y_score[:, i])\n", " roc_auc[cl] = auc(fpr[cl], tpr[cl])"]}, {"cell_type": "code", "execution_count": 19, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["fig, ax = plt.subplots(1, 1, figsize=(8,4))\n", "for k in roc_auc:\n", " ax.plot(fpr[k], tpr[k], label=\"c%d = %1.2f\" % (k, roc_auc[k]))\n", "ax.legend();"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Ces chiffres peuvent para\u00eetre \u00e9lev\u00e9s mais ce n'est pas formidable quand m\u00eame."]}, {"cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([[ 0, 0, 3, 12, 0, 0, 0],\n", " [ 0, 8, 60, 38, 2, 0, 0],\n", " [ 2, 3, 755, 303, 6, 0, 0],\n", " [ 0, 0, 242, 1083, 91, 2, 0],\n", " [ 0, 0, 20, 280, 236, 4, 0],\n", " [ 0, 0, 0, 42, 26, 29, 0],\n", " [ 0, 0, 0, 2, 0, 0, 0]], dtype=int64)"]}, "execution_count": 21, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.metrics import confusion_matrix\n", "confusion_matrix(y_test, pipe.predict(X_test), labels=labels)"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Ce n'est pas tr\u00e8s joli..."]}, {"cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
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"], "text/plain": [" 3 4 5 6 7 8\n", "0 0 0 2 1 0 0\n", "1 0 5 21 6 0 0\n", "2 0 0 517 77 1 0\n", "3 0 0 109 539 7 0\n", "4 0 0 7 71 141 0\n", "5 0 0 0 10 3 25"]}, "execution_count": 23, "metadata": {}, "output_type": "execute_result"}], "source": ["import numpy\n", "ind = numpy.max(pipe.predict_proba(X_test), axis=1) >= 0.6\n", "confusion_matrix_df(y_test[ind], pipe.predict(X_test)[ind])"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Les petites classes ont disparu : le mod\u00e8le n'est pas s\u00fbr du tout pour les classes 3, 4, 9. On voit aussi que le mod\u00e8le se trompe souvent d'une note, il serait sans doute plus judicieux de passer \u00e0 un mod\u00e8le de r\u00e9gression plut\u00f4t que de classification. Cependant, un mod\u00e8le de r\u00e9gression ne fournit pas de score de confiance. Sans doute serait-il possible d'en construire avec un mod\u00e8le de d\u00e9tection d'anomalie..."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Anomalies\n", "\n", "Une anomalie est un point aberrant. Cela revient \u00e0 dire que sa probabilit\u00e9 qu'un tel \u00e9v\u00e9nement se reproduise est faible. Un mod\u00e8le assez connu est [EllipticEnvelope](https://scikit-learn.org/stable/auto_examples/plot_anomaly_comparison.html). On suppose que si le mod\u00e8le d\u00e9tecte une anomalie, un mod\u00e8le de pr\u00e9diction aura plus de mal \u00e0 pr\u00e9dire. On r\u00e9utilise le pipeline pr\u00e9c\u00e9dent en changeant juste la derni\u00e8re \u00e9tape."]}, {"cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [{"data": {"text/plain": ["array([1, 1, 1, ..., 1, 1, 1])"]}, "execution_count": 24, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.covariance import EllipticEnvelope\n", "\n", "one = Pipeline([\n", " (\"prep\", ColumnTransformer([\n", " (\"color\", Pipeline([\n", " ('one', OneHotEncoder()),\n", " ('select', ColumnTransformer([('sel1', 'passthrough', [0])]))\n", " ]), ['color']),\n", " (\"others\", \"passthrough\", numeric_features)\n", " ])),\n", " (\"lr\", EllipticEnvelope()),\n", "])\n", "\n", "one.fit(X_train)\n", "ano = one.predict(X_test)\n", "ano"]}, {"cell_type": "code", "execution_count": 24, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " note \n", " ano \n", " pred \n", " errors \n", " proba_max \n", " anoclip \n", " \n", " \n", " \n", " \n", " 3776 \n", " 7 \n", " 114.263113 \n", " 5 \n", " False \n", " 0.68 \n", " 114.263113 \n", " \n", " \n", " 5800 \n", " 6 \n", " 113.160338 \n", " 6 \n", " True \n", " 0.82 \n", " 113.160338 \n", " \n", " \n", " 4028 \n", " 6 \n", " 107.483432 \n", " 6 \n", " True \n", " 0.55 \n", " 107.483432 \n", " \n", " \n", " 3311 \n", " 6 \n", " 112.045947 \n", " 5 \n", " False \n", " 0.46 \n", " 112.045947 \n", " \n", " \n", " 4716 \n", " 7 \n", " 118.097584 \n", " 6 \n", " False \n", " 0.59 \n", " 118.097584 \n", " \n", " \n", "
\n", "
"], "text/plain": [" note ano pred errors proba_max anoclip\n", "3776 7 114.263113 5 False 0.68 114.263113\n", "5800 6 113.160338 6 True 0.82 113.160338\n", "4028 6 107.483432 6 True 0.55 107.483432\n", "3311 6 112.045947 5 False 0.46 112.045947\n", "4716 7 118.097584 6 False 0.59 118.097584"]}, "execution_count": 25, "metadata": {}, "output_type": "execute_result"}], "source": ["from pandas import DataFrame\n", "df = DataFrame(dict(note=y_test, ano=one.decision_function(X_test), \n", " pred=pipe.predict(X_test), \n", " errors=y_test == pipe.predict(X_test),\n", " proba_max=numpy.max(pipe.predict_proba(X_test), axis=1),\n", " ))\n", "df[\"anoclip\"] = df.ano.apply(lambda x: max(x, -200))\n", "df.head()"]}, {"cell_type": "code", "execution_count": 25, "metadata": {"scrolled": false}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["import seaborn\n", "seaborn.lmplot(x=\"anoclip\", y=\"proba_max\", hue=\"errors\",\n", " truncate=True, height=5, data=df,\n", " logx=True, fit_reg=False);"]}, {"cell_type": "code", "execution_count": 26, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " note \n", " ano \n", " pred \n", " errors \n", " proba_max \n", " anoclip \n", " \n", " \n", " \n", " \n", " note \n", " 1.000000 \n", " 0.111448 \n", " 0.615705 \n", " -0.069233 \n", " -0.080223 \n", " 0.167420 \n", " \n", " \n", " ano \n", " 0.111448 \n", " 1.000000 \n", " 0.099407 \n", " 0.025075 \n", " 0.012574 \n", " 0.640359 \n", " \n", " \n", " pred \n", " 0.615705 \n", " 0.099407 \n", " 1.000000 \n", " -0.035231 \n", " -0.149703 \n", " 0.168249 \n", " \n", " \n", " errors \n", " -0.069233 \n", " 0.025075 \n", " -0.035231 \n", " 1.000000 \n", " 0.345579 \n", " 0.034597 \n", " \n", " \n", " proba_max \n", " -0.080223 \n", " 0.012574 \n", " -0.149703 \n", " 0.345579 \n", " 1.000000 \n", " 0.008371 \n", " \n", " \n", " anoclip \n", " 0.167420 \n", " 0.640359 \n", " 0.168249 \n", " 0.034597 \n", " 0.008371 \n", " 1.000000 \n", " \n", " \n", "
\n", "
"], "text/plain": [" note ano pred errors proba_max anoclip\n", "note 1.000000 0.111448 0.615705 -0.069233 -0.080223 0.167420\n", "ano 0.111448 1.000000 0.099407 0.025075 0.012574 0.640359\n", "pred 0.615705 0.099407 1.000000 -0.035231 -0.149703 0.168249\n", "errors -0.069233 0.025075 -0.035231 1.000000 0.345579 0.034597\n", "proba_max -0.080223 0.012574 -0.149703 0.345579 1.000000 0.008371\n", "anoclip 0.167420 0.640359 0.168249 0.034597 0.008371 1.000000"]}, "execution_count": 27, "metadata": {}, "output_type": "execute_result"}], "source": ["df.corr()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Les r\u00e9sultats pr\u00e9c\u00e9dents ne sont pas probants. On peut changer de mod\u00e8le de d\u00e9tection d'anomalies mais les conclusions restent les m\u00eames. Le score d'anomalie n'est pas reli\u00e9 au score de pr\u00e9diction."]}, {"cell_type": "code", "execution_count": 27, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["fig, ax = plt.subplots(1, 2, figsize=(14, 4))\n", "df.proba_max.hist(ax=ax[0], bins=50)\n", "df.anoclip.hist(ax=ax[1], bins=50)\n", "ax[0].set_title(\"Distribution du score de classification\")\n", "ax[1].set_title(\"Distribution du score d'anomalie\");"]}, {"cell_type": "markdown", "metadata": {}, "source": ["C'est joli mais ils n'ont rien \u00e0 voir. Et c'\u00e9tait pr\u00e9visible car le mod\u00e8le de pr\u00e9diction qu'on utilise est tout-\u00e0-fait capable de pr\u00e9dire ce qu'est une anomalie. "]}, {"cell_type": "code", "execution_count": 28, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", "
\n", " \n", " \n", " \n", " -1 \n", " 1 \n", " \n", " \n", " \n", " \n", " 0 \n", " 276 \n", " 57 \n", " \n", " \n", " 1 \n", " 31 \n", " 2885 \n", " \n", " \n", "
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"], "text/plain": [" -1 1\n", "0 276 57\n", "1 31 2885"]}, "execution_count": 29, "metadata": {}, "output_type": "execute_result"}], "source": ["\n", "pipe_ano = Pipeline([\n", " (\"prep\", ColumnTransformer([\n", " (\"color\", Pipeline([\n", " ('one', OneHotEncoder()),\n", " ('select', ColumnTransformer([('sel1', 'passthrough', [0])]))\n", " ]), ['color']),\n", " (\"others\", \"passthrough\", numeric_features)\n", " ])),\n", " (\"lr\", RandomForestClassifier()),\n", "])\n", "\n", "pipe_ano.fit(X_train, one.predict(X_train))\n", "confusion_matrix_df(one.predict(X_test), pipe_ano.predict(X_test))"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Le mod\u00e8le d'anomalie n'apporte donc aucune information nouvelle. Cela signifie que le mod\u00e8le pr\u00e9dictif initial n'am\u00e9liorerait pas sa pr\u00e9diction en utilisant le score d'anomalie. Il n'y a donc aucune chance que les erreurs ou les score de pr\u00e9diction soient corr\u00e9l\u00e9s au score d'anomalie d'une mani\u00e8re ou d'une autre."]}, {"cell_type": "markdown", "metadata": {}, "source": ["## Score de confiance pour une r\u00e9gression"]}, {"cell_type": "code", "execution_count": 29, "metadata": {}, "outputs": [{"data": {"text/plain": ["0.45446782471634095"]}, "execution_count": 30, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.ensemble import RandomForestRegressor\n", "from sklearn.metrics import r2_score\n", "\n", "pipe_reg = Pipeline([\n", " (\"prep\", ColumnTransformer([\n", " (\"color\", Pipeline([\n", " ('one', OneHotEncoder()),\n", " ('select', ColumnTransformer([('sel1', 'passthrough', [0])]))\n", " ]), ['color']),\n", " (\"others\", \"passthrough\", numeric_features)\n", " ])),\n", " (\"lr\", RandomForestRegressor()),\n", "])\n", "\n", "pipe_reg.fit(X_train, y_train)\n", "r2_score(y_test, pipe_reg.predict(X_test))"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Pas super. Mais..."]}, {"cell_type": "code", "execution_count": 30, "metadata": {}, "outputs": [], "source": ["error = y_test - pipe_reg.predict(X_test)\n", "score = numpy.max(pipe.predict_proba(X_test), axis=1)"]}, {"cell_type": "code", "execution_count": 31, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n", " warnings.warn(\n"]}, {"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["fig, ax = plt.subplots(1, 2, figsize=(12, 4))\n", "seaborn.kdeplot(score, error, ax=ax[1])\n", "ax[1].set_ylim([-1.5, 1.5])\n", "ax[1].set_title(\"Densit\u00e9\")\n", "ax[0].plot(score, error, \".\")\n", "ax[0].set_xlabel(\"score de confiance du classifieur\")\n", "ax[0].set_ylabel(\"Erreur de pr\u00e9diction\")\n", "ax[0].set_title(\"Lien entre classification et pr\u00e9diction\");"]}, {"cell_type": "markdown", "metadata": {}, "source": ["Comme pr\u00e9vu le mod\u00e8le ne se trompe pas plus dans un sens que dans l'autre."]}, {"cell_type": "code", "execution_count": 32, "metadata": {}, "outputs": [{"name": "stderr", "output_type": "stream", "text": ["C:\\Python395_x64\\lib\\site-packages\\seaborn\\_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: y. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n", " warnings.warn(\n"]}, {"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {"needs_background": "light"}, "output_type": "display_data"}], "source": ["fig, ax = plt.subplots(1, 2, figsize=(12, 4))\n", "seaborn.kdeplot(score, error.abs(), ax=ax[1])\n", "ax[1].set_ylim([0, 1.5])\n", "ax[1].set_title(\"Densit\u00e9\")\n", "ax[0].plot(score, error.abs(), \".\")\n", "ax[0].set_xlabel(\"score de confiance du classifieur\")\n", "ax[0].set_ylabel(\"Erreur de pr\u00e9diction\")\n", "ax[0].set_title(\"Lien entre classification et pr\u00e9diction\");"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On vient de construire un indicateur de confiance pour un mod\u00e8le de r\u00e9gression. On voit aussi que l'erreur de pr\u00e9diction est concentr\u00e9e autour de 0.5 lorsque le score est faible. C'est normal dans la mesure o\u00f9 la probabilit\u00e9 est faible lorsque le classifieur n'est pas s\u00fbr, c'est-\u00e0-dire que l'observation \u00e0 pr\u00e9dire est proche de la fronti\u00e8re entre deux classes. Ces classes sont centr\u00e9es autour des notes enti\u00e8res, les fronti\u00e8res sont au milieu, soit approximativement 3.5, 4.5, ... Ce n'est pas une preuve mais seulement la v\u00e9rifie que l'intervalle de confiance qu'on vient de fabriquer n'est pas compl\u00e8tement aberrant."]}, {"cell_type": "code", "execution_count": 33, "metadata": {}, "outputs": [], "source": []}], "metadata": {"kernelspec": {"display_name": "Python 3", "language": "python", "name": "python3"}, "language_info": {"codemirror_mode": {"name": "ipython", "version": 3}, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.9.5"}}, "nbformat": 4, "nbformat_minor": 2}