Pushing the docs to dev/ for branch: master, commit b705cb811df5b3be582712cd9644743401ab1a43

Author: sklearn-ci

dev/_downloads/auto_examples_jupyter.zip

@@ -24,7 +24,7 @@
       "execution_count": null, 
       "cell_type": "code", 
       "source": [
-        "print(__doc__)\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef modified_huber_loss(y_true, y_pred):\n    z = y_pred * y_true\n    loss = -4 * z\n    loss[z >= -1] = (1 - z[z >= -1]) ** 2\n    loss[z >= 1.] = 0\n    return loss\n\n\nxmin, xmax = -4, 4\nxx = np.linspace(xmin, xmax, 100)\nlw = 2\nplt.plot([xmin, 0, 0, xmax], [1, 1, 0, 0], color='gold', lw=lw,\n         label=\"Zero-one loss\")\nplt.plot(xx, np.where(xx < 1, 1 - xx, 0), color='teal', lw=lw,\n         label=\"Hinge loss\")\nplt.plot(xx, -np.minimum(xx, 0), color='yellowgreen', lw=lw,\n         label=\"Perceptron loss\")\nplt.plot(xx, np.log2(1 + np.exp(-xx)), color='cornflowerblue', lw=lw,\n         label=\"Log loss\")\nplt.plot(xx, np.where(xx < 1, 1 - xx, 0) ** 2, color='orange', lw=lw,\n         label=\"Squared hinge loss\")\nplt.plot(xx, modified_huber_loss(xx, 1), color='darkorchid', lw=lw,\n         linestyle='--', label=\"Modified Huber loss\")\nplt.ylim((0, 8))\nplt.legend(loc=\"upper right\")\nplt.xlabel(r\"Decision function $f(x)$\")\nplt.ylabel(\"$L(y, f(x))$\")\nplt.show()"
+        "print(__doc__)\n\nimport numpy as np\nimport matplotlib.pyplot as plt\n\n\ndef modified_huber_loss(y_true, y_pred):\n    z = y_pred * y_true\n    loss = -4 * z\n    loss[z >= -1] = (1 - z[z >= -1]) ** 2\n    loss[z >= 1.] = 0\n    return loss\n\n\nxmin, xmax = -4, 4\nxx = np.linspace(xmin, xmax, 100)\nlw = 2\nplt.plot([xmin, 0, 0, xmax], [1, 1, 0, 0], color='gold', lw=lw,\n         label=\"Zero-one loss\")\nplt.plot(xx, np.where(xx < 1, 1 - xx, 0), color='teal', lw=lw,\n         label=\"Hinge loss\")\nplt.plot(xx, -np.minimum(xx, 0), color='yellowgreen', lw=lw,\n         label=\"Perceptron loss\")\nplt.plot(xx, np.log2(1 + np.exp(-xx)), color='cornflowerblue', lw=lw,\n         label=\"Log loss\")\nplt.plot(xx, np.where(xx < 1, 1 - xx, 0) ** 2, color='orange', lw=lw,\n         label=\"Squared hinge loss\")\nplt.plot(xx, modified_huber_loss(xx, 1), color='darkorchid', lw=lw,\n         linestyle='--', label=\"Modified Huber loss\")\nplt.ylim((0, 8))\nplt.legend(loc=\"upper right\")\nplt.xlabel(r\"Decision function $f(x)$\")\nplt.ylabel(\"$L(y=1, f(x))$\")\nplt.show()"
       ], 
       "outputs": [], 
       "metadata": {

dev/_downloads/auto_examples_python.zip

@@ -38,5 +38,5 @@ def modified_huber_loss(y_true, y_pred):
 plt.ylim((0, 8))
 plt.legend(loc="upper right")
 plt.xlabel(r"Decision function $f(x)$")
-plt.ylabel("$L(y, f(x))$")
+plt.ylabel("$L(y=1, f(x))$")
 plt.show()