sklearn.datasets.load_mlcomp()

sklearn.datasets.load_mlcomp(name_or_id, set_='raw', mlcomp_root=None, **kwargs)

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

sklearn.datasets.load_breast_cancer(return_X_y=False)

2017-01-15 04:25:44
sklearn.datasets.fetch_species_distributions()

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

2017-01-15 04:25:43
sklearn.datasets.fetch_olivetti_faces()

sklearn.datasets.fetch_olivetti_faces(data_home=None, shuffle=False, random_state=0, download_if_missing=True)

2017-01-15 04:25:42
sklearn.datasets.fetch_kddcup99()

sklearn.datasets.fetch_kddcup99(subset=None, shuffle=False, random_state=None, percent10=True, download_if_missing=True)

2017-01-15 04:25:40
sklearn.datasets.make_checkerboard()

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

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

sklearn.datasets.load_diabetes(return_X_y=False)

2017-01-15 04:25:45
sklearn.datasets.make_low_rank_matrix()

sklearn.datasets.make_low_rank_matrix(n_samples=100, n_features=100, effective_rank=10, tail_strength=0.5, random_state=None)

2017-01-15 04:25:56
sklearn.datasets.load_svmlight_files()

sklearn.datasets.load_svmlight_files(files, n_features=None, dtype=, multilabel=False, zero_based='auto', query_id=False)

2017-01-15 04:25:51
sklearn.datasets.fetch_20newsgroups()

sklearn.datasets.fetch_20newsgroups(data_home=None, subset='train', categories=None, shuffle=True, random_state=42, remove=()

2017-01-15 04:25:39