Pushing the docs to dev/ for branch: master, commit 9b75a81b2dd89daf93e483b3b32ea1759edaf937

Author: sklearn-ci

dev/_downloads/auto_examples_jupyter.zip

@@ -42,7 +42,7 @@
       "execution_count": null, 
       "cell_type": "code", 
       "source": [
-        "np.random.seed(42)\n\nn_samples, n_features = 50, 200\nX = np.random.randn(n_samples, n_features)\ncoef = 3 * np.random.randn(n_features)\ninds = np.arange(n_features)\nnp.random.shuffle(inds)\ncoef[inds[10:]] = 0  # sparsify coef\ny = np.dot(X, coef)\n\n# add noise\ny += 0.01 * np.random.normal((n_samples,))\n\n# Split data in train set and test set\nn_samples = X.shape[0]\nX_train, y_train = X[:n_samples // 2], y[:n_samples // 2]\nX_test, y_test = X[n_samples // 2:], y[n_samples // 2:]"
+        "np.random.seed(42)\n\nn_samples, n_features = 50, 200\nX = np.random.randn(n_samples, n_features)\ncoef = 3 * np.random.randn(n_features)\ninds = np.arange(n_features)\nnp.random.shuffle(inds)\ncoef[inds[10:]] = 0  # sparsify coef\ny = np.dot(X, coef)\n\n# add noise\ny += 0.01 * np.random.normal(size=n_samples)\n\n# Split data in train set and test set\nn_samples = X.shape[0]\nX_train, y_train = X[:n_samples // 2], y[:n_samples // 2]\nX_test, y_test = X[n_samples // 2:], y[n_samples // 2:]"
       ], 
       "outputs": [], 
       "metadata": {

dev/_downloads/auto_examples_python.zip

@@ -28,7 +28,7 @@
 y = np.dot(X, coef)
 
 # add noise
-y += 0.01 * np.random.normal((n_samples,))
+y += 0.01 * np.random.normal(size=n_samples)
 
 # Split data in train set and test set
 n_samples = X.shape[0]