102 lines
3.6 KiB
Python
102 lines
3.6 KiB
Python
"""
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The :mod:`sklearn.datasets` module includes utilities to load datasets,
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including methods to load and fetch popular reference datasets. It also
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features some artificial data generators.
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"""
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from .base import load_breast_cancer
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from .base import load_boston
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from .base import load_diabetes
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from .base import load_digits
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from .base import load_files
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from .base import load_iris
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from .base import load_linnerud
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from .base import load_sample_images
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from .base import load_sample_image
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from .base import load_wine
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from .base import get_data_home
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from .base import clear_data_home
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from .covtype import fetch_covtype
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from .kddcup99 import fetch_kddcup99
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from .mlcomp import load_mlcomp
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from .lfw import fetch_lfw_pairs
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from .lfw import fetch_lfw_people
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from .twenty_newsgroups import fetch_20newsgroups
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from .twenty_newsgroups import fetch_20newsgroups_vectorized
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from .mldata import fetch_mldata, mldata_filename
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from .samples_generator import make_classification
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from .samples_generator import make_multilabel_classification
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from .samples_generator import make_hastie_10_2
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from .samples_generator import make_regression
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from .samples_generator import make_blobs
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from .samples_generator import make_moons
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from .samples_generator import make_circles
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from .samples_generator import make_friedman1
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from .samples_generator import make_friedman2
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from .samples_generator import make_friedman3
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from .samples_generator import make_low_rank_matrix
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from .samples_generator import make_sparse_coded_signal
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from .samples_generator import make_sparse_uncorrelated
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from .samples_generator import make_spd_matrix
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from .samples_generator import make_swiss_roll
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from .samples_generator import make_s_curve
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from .samples_generator import make_sparse_spd_matrix
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from .samples_generator import make_gaussian_quantiles
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from .samples_generator import make_biclusters
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from .samples_generator import make_checkerboard
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from .svmlight_format import load_svmlight_file
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from .svmlight_format import load_svmlight_files
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from .svmlight_format import dump_svmlight_file
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from .olivetti_faces import fetch_olivetti_faces
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from .species_distributions import fetch_species_distributions
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from .california_housing import fetch_california_housing
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from .rcv1 import fetch_rcv1
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__all__ = ['clear_data_home',
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'dump_svmlight_file',
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'fetch_20newsgroups',
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'fetch_20newsgroups_vectorized',
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'fetch_lfw_pairs',
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'fetch_lfw_people',
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'fetch_mldata',
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'fetch_olivetti_faces',
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'fetch_species_distributions',
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'fetch_california_housing',
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'fetch_covtype',
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'fetch_rcv1',
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'fetch_kddcup99',
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'get_data_home',
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'load_boston',
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'load_diabetes',
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'load_digits',
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'load_files',
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'load_iris',
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'load_breast_cancer',
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'load_linnerud',
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'load_mlcomp',
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'load_sample_image',
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'load_sample_images',
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'load_svmlight_file',
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'load_svmlight_files',
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'load_wine',
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'make_biclusters',
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'make_blobs',
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'make_circles',
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'make_classification',
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'make_checkerboard',
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'make_friedman1',
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'make_friedman2',
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'make_friedman3',
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'make_gaussian_quantiles',
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'make_hastie_10_2',
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'make_low_rank_matrix',
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'make_moons',
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'make_multilabel_classification',
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'make_regression',
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'make_s_curve',
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'make_sparse_coded_signal',
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'make_sparse_spd_matrix',
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'make_sparse_uncorrelated',
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'make_spd_matrix',
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'make_swiss_roll',
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'mldata_filename']
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