{"cells": [{"cell_type": "markdown", "metadata": {}, "source": ["# R\u00e9gression logistique en 2D\n", "\n", "Pr\u00e9dire la couleur d'un vin \u00e0 partir de ses composants."]}, {"cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": ["%matplotlib inline"]}, {"cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": ["from papierstat.datasets import load_wines_dataset\n", "data = load_wines_dataset()\n", "X = data.drop(['quality', 'color'], axis=1)\n", "y = data['color']"]}, {"cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": ["from sklearn.model_selection import train_test_split\n", "X_train, X_test, y_train, y_test = train_test_split(X, y)"]}, {"cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [{"name": "stdout", "output_type": "stream", "text": ["Optimization terminated successfully.\n", " Current function value: 0.044575\n", " Iterations 11\n"]}], "source": ["from statsmodels.discrete.discrete_model import Logit\n", "model = Logit(y_train == \"white\", X_train)\n", "res = model.fit()"]}, {"cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [{"data": {"text/html": ["\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
Model: Logit No. Iterations: 11.0000
Dependent Variable: color Pseudo R-squared: 0.921
Date: 2018-02-08 00:13 AIC: 456.3398
No. Observations: 4872 BIC: 527.7436
Df Model: 10 Log-Likelihood: -217.17
Df Residuals: 4861 LL-Null: -2748.5
Converged: 1.0000 Scale: 1.0000
\n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "\n", " \n", "\n", "
Coef. Std.Err. z P>|z| [0.025 0.975]
fixed_acidity -1.4449 0.1519 -9.5141 0.0000 -1.7425 -1.1472
volatile_acidity -12.0133 0.9940 -12.0857 0.0000 -13.9615 -10.0651
citric_acid 0.1218 1.1387 0.1070 0.9148 -2.1101 2.3537
residual_sugar 0.0780 0.0578 1.3484 0.1775 -0.0354 0.1913
chlorides -33.6942 4.1533 -8.1125 0.0000 -41.8346 -25.5538
free_sulfur_dioxide -0.0474 0.0149 -3.1804 0.0015 -0.0767 -0.0182
total_sulfur_dioxide 0.0691 0.0055 12.6272 0.0000 0.0584 0.0798
density 45.6528 4.4627 10.2299 0.0000 36.9061 54.3994
pH -10.0587 1.0255 -9.8086 0.0000 -12.0687 -8.0488
sulphates -9.1971 1.0697 -8.5980 0.0000 -11.2936 -7.1006
alcohol 0.5328 0.1284 4.1494 0.0000 0.2811 0.7844
"], "text/plain": ["\n", "\"\"\"\n", " Results: Logit\n", "========================================================================\n", "Model: Logit No. Iterations: 11.0000 \n", "Dependent Variable: color Pseudo R-squared: 0.921 \n", "Date: 2018-02-08 00:13 AIC: 456.3398\n", "No. Observations: 4872 BIC: 527.7436\n", "Df Model: 10 Log-Likelihood: -217.17 \n", "Df Residuals: 4861 LL-Null: -2748.5 \n", "Converged: 1.0000 Scale: 1.0000 \n", "------------------------------------------------------------------------\n", " Coef. Std.Err. z P>|z| [0.025 0.975] \n", "------------------------------------------------------------------------\n", "fixed_acidity -1.4449 0.1519 -9.5141 0.0000 -1.7425 -1.1472\n", "volatile_acidity -12.0133 0.9940 -12.0857 0.0000 -13.9615 -10.0651\n", "citric_acid 0.1218 1.1387 0.1070 0.9148 -2.1101 2.3537\n", "residual_sugar 0.0780 0.0578 1.3484 0.1775 -0.0354 0.1913\n", "chlorides -33.6942 4.1533 -8.1125 0.0000 -41.8346 -25.5538\n", "free_sulfur_dioxide -0.0474 0.0149 -3.1804 0.0015 -0.0767 -0.0182\n", "total_sulfur_dioxide 0.0691 0.0055 12.6272 0.0000 0.0584 0.0798\n", "density 45.6528 4.4627 10.2299 0.0000 36.9061 54.3994\n", "pH -10.0587 1.0255 -9.8086 0.0000 -12.0687 -8.0488\n", "sulphates -9.1971 1.0697 -8.5980 0.0000 -11.2936 -7.1006\n", "alcohol 0.5328 0.1284 4.1494 0.0000 0.2811 0.7844\n", "========================================================================\n", "\n", "\"\"\""]}, "execution_count": 6, "metadata": {}, "output_type": "execute_result"}], "source": ["res.summary2()"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On ne garde que les deux premi\u00e8res."]}, {"cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": ["X_train2 = X_train.iloc[:, :2]"]}, {"cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {}, "output_type": "display_data"}], "source": ["import pandas\n", "df = pandas.DataFrame(X_train2.copy())\n", "df['y'] = y_train\n", "\n", "import matplotlib.pyplot as plt\n", "fig, ax = plt.subplots(1, 1, figsize=(4, 4))\n", "df[df.y == \"white\"].plot(x=\"fixed_acidity\", y=\"volatile_acidity\", ax=ax, kind='scatter', label=\"white\")\n", "df[df.y == \"red\"].plot(x=\"fixed_acidity\", y=\"volatile_acidity\", ax=ax,\n", " kind='scatter', label=\"red\", color=\"red\", s=2)\n", "ax.set_title(\"Vins rouges et white selon deux composantes\");"]}, {"cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [{"data": {"text/plain": ["LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n", " intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n", " penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n", " verbose=0, warm_start=False)"]}, "execution_count": 9, "metadata": {}, "output_type": "execute_result"}], "source": ["from sklearn.linear_model import LogisticRegression\n", "model = LogisticRegression()\n", "model.fit(X_train2, y_train == \"white\")"]}, {"cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [{"data": {"text/plain": ["(array([[ -0.92015604, -10.76494765]]), array([11.96976599]))"]}, "execution_count": 10, "metadata": {}, "output_type": "execute_result"}], "source": ["model.coef_, model.intercept_"]}, {"cell_type": "markdown", "metadata": {}, "source": ["On trace cette droite sur le graphique."]}, {"cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [{"data": {"text/plain": ["(3, array([0.85548933]), 14, array([-0.08475829]))"]}, "execution_count": 11, "metadata": {}, "output_type": "execute_result"}], "source": ["x0 = 3\n", "y0 = -(model.coef_[0,0] * x0 + model.intercept_) / model.coef_[0,1]\n", "x1 = 14\n", "y1 = -(model.coef_[0,0] * x1 + model.intercept_) / model.coef_[0,1]\n", "x0, y0, x1, y1"]}, {"cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [{"data": {"image/png": 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\n", "text/plain": [""]}, "metadata": {}, "output_type": "display_data"}], "source": ["import matplotlib.pyplot as plt\n", "fig, ax = plt.subplots(1, 1, figsize=(4, 4))\n", "df[df.y == \"white\"].plot(x=\"fixed_acidity\", y=\"volatile_acidity\", ax=ax, kind='scatter', label=\"white\")\n", "df[df.y == \"red\"].plot(x=\"fixed_acidity\", y=\"volatile_acidity\", ax=ax,\n", " kind='scatter', label=\"red\", color=\"red\", s=2)\n", "ax.plot([x0, x1], [y0, y1], 'y--', lw=4, label='fronti\u00e8re trouv\u00e9e\\npar la r\u00e9gression\\nlogistique')\n", "ax.legend()\n", "ax.set_title(\"Vins rouges et blancs\\nselon deux composantes\");"]}, {"cell_type": "code", "execution_count": 12, "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": "3.6.4"}}, "nbformat": 4, "nbformat_minor": 2}