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"""Utilities to load popular datasets and artificial data generators.""" |
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import textwrap |
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from ._base import ( |
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clear_data_home, |
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fetch_file, |
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get_data_home, |
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load_breast_cancer, |
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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_linnerud, |
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load_sample_image, |
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load_sample_images, |
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load_wine, |
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) |
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from ._california_housing import fetch_california_housing |
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from ._covtype import fetch_covtype |
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from ._kddcup99 import fetch_kddcup99 |
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from ._lfw import fetch_lfw_pairs, fetch_lfw_people |
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from ._olivetti_faces import fetch_olivetti_faces |
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from ._openml import fetch_openml |
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from ._rcv1 import fetch_rcv1 |
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from ._samples_generator import ( |
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make_biclusters, |
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make_blobs, |
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make_checkerboard, |
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make_circles, |
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make_classification, |
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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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) |
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from ._species_distributions import fetch_species_distributions |
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from ._svmlight_format_io import ( |
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dump_svmlight_file, |
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load_svmlight_file, |
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load_svmlight_files, |
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) |
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from ._twenty_newsgroups import fetch_20newsgroups, fetch_20newsgroups_vectorized |
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__all__ = [ |
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"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_file", |
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"fetch_lfw_pairs", |
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"fetch_lfw_people", |
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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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"fetch_openml", |
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"get_data_home", |
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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_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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] |
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def __getattr__(name): |
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if name == "load_boston": |
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msg = textwrap.dedent( |
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""" |
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`load_boston` has been removed from scikit-learn since version 1.2. |
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The Boston housing prices dataset has an ethical problem: as |
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investigated in [1], the authors of this dataset engineered a |
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non-invertible variable "B" assuming that racial self-segregation had a |
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positive impact on house prices [2]. Furthermore the goal of the |
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research that led to the creation of this dataset was to study the |
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impact of air quality but it did not give adequate demonstration of the |
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validity of this assumption. |
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The scikit-learn maintainers therefore strongly discourage the use of |
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this dataset unless the purpose of the code is to study and educate |
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about ethical issues in data science and machine learning. |
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In this special case, you can fetch the dataset from the original |
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source:: |
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import pandas as pd |
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import numpy as np |
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data_url = "http://lib.stat.cmu.edu/datasets/boston" |
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raw_df = pd.read_csv(data_url, sep="\\s+", skiprows=22, header=None) |
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data = np.hstack([raw_df.values[::2, :], raw_df.values[1::2, :2]]) |
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target = raw_df.values[1::2, 2] |
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Alternative datasets include the California housing dataset and the |
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Ames housing dataset. You can load the datasets as follows:: |
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from sklearn.datasets import fetch_california_housing |
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housing = fetch_california_housing() |
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for the California housing dataset and:: |
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from sklearn.datasets import fetch_openml |
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housing = fetch_openml(name="house_prices", as_frame=True) |
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for the Ames housing dataset. |
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[1] M Carlisle. |
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"Racist data destruction?" |
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<https://medium.com/@docintangible/racist-data-destruction-113e3eff54a8> |
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[2] Harrison Jr, David, and Daniel L. Rubinfeld. |
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"Hedonic housing prices and the demand for clean air." |
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Journal of environmental economics and management 5.1 (1978): 81-102. |
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<https://www.researchgate.net/publication/4974606_Hedonic_housing_prices_and_the_demand_for_clean_air> |
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""" |
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) |
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raise ImportError(msg) |
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try: |
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return globals()[name] |
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except KeyError: |
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raise AttributeError |
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