Pushing the docs to dev/ for branch: main, commit 0b978cb86f2fd23bef9940cf04254cbd05d2a661

Author: sklearn-ci

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -73,7 +73,7 @@
       },
       "outputs": [],
       "source": [
-        "import matplotlib.pyplot as plt\nfrom matplotlib.gridspec import GridSpec\n\nfig = plt.figure(figsize=(10, 10))\ngs = GridSpec(4, 2)\ncolors = plt.cm.get_cmap(\"Dark2\")\n\nax_calibration_curve = fig.add_subplot(gs[:2, :2])\ncalibration_displays = {}\nfor i, (clf, name) in enumerate(clf_list):\n    clf.fit(X_train, y_train)\n    display = CalibrationDisplay.from_estimator(\n        clf,\n        X_test,\n        y_test,\n        n_bins=10,\n        name=name,\n        ax=ax_calibration_curve,\n        color=colors(i),\n    )\n    calibration_displays[name] = display\n\nax_calibration_curve.grid()\nax_calibration_curve.set_title(\"Calibration plots\")\n\n# Add histogram\ngrid_positions = [(2, 0), (2, 1), (3, 0), (3, 1)]\nfor i, (_, name) in enumerate(clf_list):\n    row, col = grid_positions[i]\n    ax = fig.add_subplot(gs[row, col])\n\n    ax.hist(\n        calibration_displays[name].y_prob,\n        range=(0, 1),\n        bins=10,\n        label=name,\n        color=colors(i),\n    )\n    ax.set(title=name, xlabel=\"Mean predicted probability\", ylabel=\"Count\")\n\nplt.tight_layout()\nplt.show()"
+        "import matplotlib.pyplot as plt\nfrom matplotlib.gridspec import GridSpec\n\nfig = plt.figure(figsize=(10, 10))\ngs = GridSpec(4, 2)\ncolors = plt.cm.get_cmap(\"Dark2\")\n\nax_calibration_curve = fig.add_subplot(gs[:2, :2])\ncalibration_displays = {}\nmarkers = [\"^\", \"v\", \"s\", \"o\"]\nfor i, (clf, name) in enumerate(clf_list):\n    clf.fit(X_train, y_train)\n    display = CalibrationDisplay.from_estimator(\n        clf,\n        X_test,\n        y_test,\n        n_bins=10,\n        name=name,\n        ax=ax_calibration_curve,\n        color=colors(i),\n        marker=markers[i],\n    )\n    calibration_displays[name] = display\n\nax_calibration_curve.grid()\nax_calibration_curve.set_title(\"Calibration plots\")\n\n# Add histogram\ngrid_positions = [(2, 0), (2, 1), (3, 0), (3, 1)]\nfor i, (_, name) in enumerate(clf_list):\n    row, col = grid_positions[i]\n    ax = fig.add_subplot(gs[row, col])\n\n    ax.hist(\n        calibration_displays[name].y_prob,\n        range=(0, 1),\n        bins=10,\n        label=name,\n        color=colors(i),\n    )\n    ax.set(title=name, xlabel=\"Mean predicted probability\", ylabel=\"Count\")\n\nplt.tight_layout()\nplt.show()"
       ]
     },
     {