sklearn.datasets.make_moons
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sklearn.datasets.make_moons(n_samples=100, shuffle=True, noise=None, random_state=None)
[source]
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Make two interleaving half circles
A simple toy dataset to visualize clustering and classification algorithms. Read more in the User Guide.
Parameters: |
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n_samples : int, optional (default=100) -
The total number of points generated. -
shuffle : bool, optional (default=True) -
Whether to shuffle the samples. -
noise : double or None (default=None) -
Standard deviation of Gaussian noise added to the data. -
random_state : int, RandomState instance or None (default) -
Determines random number generation for dataset shuffling and noise. Pass an int for reproducible output across multiple function calls. See Glossary. |
Returns: |
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X : array of shape [n_samples, 2] -
The generated samples. -
y : array of shape [n_samples] -
The integer labels (0 or 1) for class membership of each sample. |
Examples using sklearn.datasets.make_moons