Pushing the docs to dev/ for branch: master, commit 0d29d2e11d064637b2ec27fe6738039bca724dfe

Author: sklearn-ci

dev/_downloads/03d92e4804175ff27d91620c6dcbe283/plot_random_dataset.ipynb

@@ -15,7 +15,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# Plot randomly generated classification dataset\n\n\nPlot several randomly generated 2D classification datasets.\nThis example illustrates the :func:`datasets.make_classification`\n:func:`datasets.make_blobs` and :func:`datasets.make_gaussian_quantiles`\nfunctions.\n\nFor ``make_classification``, three binary and two multi-class classification\ndatasets are generated, with different numbers of informative features and\nclusters per class.  \n"
+        "\n# Plot randomly generated classification dataset\n\n\nThis example plots several randomly generated classification datasets.\nFor easy visualization, all datasets have 2 features, plotted on the x and y\naxis. The color of each point represents its class label.\n\nThe first 4 plots use the :func:`~sklearn.datasets.make_classification` with\ndifferent numbers of informative features, clusters per class and classes.\nThe final 2 plots use :func:`~sklearn.datasets.make_blobs` and\n:func:`~sklearn.datasets.make_gaussian_quantiles`.\n"
       ]
     },
     {

dev/_downloads/3409d9766d352cc9f9b169d4a799a87a/auto_examples_python.zip

@@ -3,14 +3,15 @@
 Plot randomly generated classification dataset
 ==============================================
 
-Plot several randomly generated 2D classification datasets.
-This example illustrates the :func:`datasets.make_classification`
-:func:`datasets.make_blobs` and :func:`datasets.make_gaussian_quantiles`
-functions.
+This example plots several randomly generated classification datasets.
+For easy visualization, all datasets have 2 features, plotted on the x and y
+axis. The color of each point represents its class label.
 
-For ``make_classification``, three binary and two multi-class classification
-datasets are generated, with different numbers of informative features and
-clusters per class.  """
+The first 4 plots use the :func:`~sklearn.datasets.make_classification` with
+different numbers of informative features, clusters per class and classes.
+The final 2 plots use :func:`~sklearn.datasets.make_blobs` and
+:func:`~sklearn.datasets.make_gaussian_quantiles`.
+"""
 
 print(__doc__)