sklearn.datasets.fetch_species_distributions()
  • References/Python/scikit-learn/API Reference/datasets

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

2025-01-10 15:47:30
sklearn.datasets.load_mlcomp()
  • References/Python/scikit-learn/API Reference/datasets

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

2025-01-10 15:47:30
sklearn.datasets.make_friedman1()
  • References/Python/scikit-learn/API Reference/datasets

sklearn.datasets.make_friedman1(n_samples=100, n_features=10, noise=0.0, random_state=None)

2025-01-10 15:47:30
sklearn.datasets.load_lfw_people()
  • References/Python/scikit-learn/API Reference/datasets

Warning DEPRECATED

2025-01-10 15:47:30
sklearn.datasets.load_diabetes()
  • References/Python/scikit-learn/API Reference/datasets

sklearn.datasets.load_diabetes(return_X_y=False)

2025-01-10 15:47:30
sklearn.datasets.load_breast_cancer()
  • References/Python/scikit-learn/API Reference/datasets

sklearn.datasets.load_breast_cancer(return_X_y=False)

2025-01-10 15:47:30
sklearn.datasets.fetch_kddcup99()
  • References/Python/scikit-learn/API Reference/datasets

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

2025-01-10 15:47:30
sklearn.datasets.fetch_mldata()
  • References/Python/scikit-learn/API Reference/datasets

sklearn.datasets.fetch_mldata(dataname, target_name='label', data_name='data', transpose_data=True, data_home=None)

2025-01-10 15:47:30
sklearn.datasets.make_regression()
  • References/Python/scikit-learn/API Reference/datasets

sklearn.datasets.make_regression(n_samples=100, n_features=100, n_informative=10, n_targets=1, bias=0.0, effective_rank=None, tail_strength=0

2025-01-10 15:47:30
sklearn.datasets.make_low_rank_matrix()
  • References/Python/scikit-learn/API Reference/datasets

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

2025-01-10 15:47:30