sklearn.datasets.fetch_california_housing()

sklearn.datasets.fetch_california_housing(data_home=None, download_if_missing=True)

2017-01-15 04:25:39
sklearn.datasets.make_multilabel_classification()

sklearn.datasets.make_multilabel_classification(n_samples=100, n_features=20, n_classes=5, n_labels=2, length=50

2017-01-15 04:25:57
sklearn.datasets.load_sample_image()

sklearn.datasets.load_sample_image(image_name)

2017-01-15 04:25:49
sklearn.datasets.load_digits()

sklearn.datasets.load_digits(n_class=10, return_X_y=False)

2017-01-15 04:25:46
sklearn.datasets.make_sparse_coded_signal()

sklearn.datasets.make_sparse_coded_signal(n_samples, n_components, n_features, n_nonzero_coefs, random_state=None)

2017-01-15 04:25:58
sklearn.datasets.fetch_20newsgroups_vectorized()

sklearn.datasets.fetch_20newsgroups_vectorized(subset='train', remove=(), data_home=None)

2017-01-15 04:25:39
sklearn.datasets.fetch_rcv1()

sklearn.datasets.fetch_rcv1(data_home=None, subset='all', download_if_missing=True, random_state=None, shuffle=False)

2017-01-15 04:25:42
sklearn.datasets.make_blobs()

sklearn.datasets.make_blobs(n_samples=100, n_features=2, centers=3, cluster_std=1.0, center_box=(-10.0, 10.0), shuffle=True, random_state=None)

2017-01-15 04:25:52
sklearn.datasets.make_biclusters()

sklearn.datasets.make_biclusters(shape, n_clusters, noise=0.0, minval=10, maxval=100, shuffle=True, random_state=None)

2017-01-15 04:25:51
sklearn.datasets.load_linnerud()

sklearn.datasets.load_linnerud(return_X_y=False)

2017-01-15 04:25:48