Pushing the docs to dev/ for branch: master, commit d01cdc204ee4972307aca4cc1e1b1e5e6347cc70

Author: sklearn-ci

dev/_downloads/auto_examples_jupyter.zip

@@ -44,7 +44,7 @@
       },
       "outputs": [],
       "source": [
-        "for assign_labels in ('kmeans', 'discretize'):\n    t0 = time.time()\n    labels = spectral_clustering(graph, n_clusters=N_REGIONS,\n                                 assign_labels=assign_labels, random_state=1)\n    t1 = time.time()\n    labels = labels.reshape(face.shape)\n\n    plt.figure(figsize=(5, 5))\n    plt.imshow(face, cmap=plt.cm.gray)\n    for l in range(N_REGIONS):\n        plt.contour(labels == l, contours=1,\n                    colors=[plt.cm.spectral(l / float(N_REGIONS))])\n    plt.xticks(())\n    plt.yticks(())\n    title = 'Spectral clustering: %s, %.2fs' % (assign_labels, (t1 - t0))\n    print(title)\n    plt.title(title)\nplt.show()"
+        "for assign_labels in ('kmeans', 'discretize'):\n    t0 = time.time()\n    labels = spectral_clustering(graph, n_clusters=N_REGIONS,\n                                 assign_labels=assign_labels, random_state=42)\n    t1 = time.time()\n    labels = labels.reshape(face.shape)\n\n    plt.figure(figsize=(5, 5))\n    plt.imshow(face, cmap=plt.cm.gray)\n    for l in range(N_REGIONS):\n        plt.contour(labels == l, contours=1,\n                    colors=[plt.cm.spectral(l / float(N_REGIONS))])\n    plt.xticks(())\n    plt.yticks(())\n    title = 'Spectral clustering: %s, %.2fs' % (assign_labels, (t1 - t0))\n    print(title)\n    plt.title(title)\nplt.show()"
       ]
     }
   ],

dev/_downloads/auto_examples_python.zip

@@ -63,7 +63,7 @@
 for assign_labels in ('kmeans', 'discretize'):
     t0 = time.time()
     labels = spectral_clustering(graph, n_clusters=N_REGIONS,
-                                 assign_labels=assign_labels, random_state=1)
+                                 assign_labels=assign_labels, random_state=42)
     t1 = time.time()
     labels = labels.reshape(face.shape)