`sklearn.datasets`.make_circles#

sklearn.datasets.make_circles(n_samples=100, *, shuffle=True, noise=None, random_state=None, factor=0.8)[source]#

Make a large circle containing a smaller circle in 2d.

A simple toy dataset to visualize clustering and classification algorithms.

Read more in the User Guide.

Parameters:

n_samplesint or tuple of shape (2,), dtype=int, default=100: If int, it is the total number of points generated. For odd numbers, the inner circle will have one point more than the outer circle. If two-element tuple, number of points in outer circle and inner circle.

Changed in version 0.23: Added two-element tuple.
shufflebool, default=True: Whether to shuffle the samples.
noisefloat, default=None: Standard deviation of Gaussian noise added to the data.
random_stateint, RandomState instance or None, default=None: Determines random number generation for dataset shuffling and noise. Pass an int for reproducible output across multiple function calls. See Glossary.
factorfloat, default=.8: Scale factor between inner and outer circle in the range [0, 1).

Returns:

Xndarray of shape (n_samples, 2): The generated samples.
yndarray of shape (n_samples,): The integer labels (0 or 1) for class membership of each sample.

Examples

>>> from sklearn.datasets import make_circles
>>> X, y = make_circles(random_state=42)
>>> X.shape
(100, 2)
>>> y.shape
(100,)
>>> list(y[:5])
[1, 1, 1, 0, 0]