sklearn.datasets.make_moons¶

sklearn.datasets.make_moons(n_samples=100, *, shuffle=True, noise=None, random_state=None)[source]¶

Make two interleaving half circles

A simple toy dataset to visualize clustering and classification algorithms. Read more in the User Guide.

Parameters

n_samplesint or two-element tuple, optional (default=100)

If int, the total number of points generated. If two-element tuple, number of points in each of two moons.

shufflebool, optional (default=True)

Whether to shuffle the samples.

noisedouble or None (default=None)

Standard deviation of Gaussian noise added to the data.

random_stateint, RandomState instance, default=None

Determines random number generation for dataset shuffling and noise. Pass an int for reproducible output across multiple function calls. See Glossary.

Returns

Xarray of shape [n_samples, 2]

The generated samples.

yarray of shape [n_samples]

The integer labels (0 or 1) for class membership of each sample.

Examples using sklearn.datasets.make_moons¶

Classifier comparison¶

Comparing different hierarchical linkage methods on toy datasets¶

Comparing different clustering algorithms on toy datasets¶

Comparing anomaly detection algorithms for outlier detection on toy datasets¶

Compare Stochastic learning strategies for MLPClassifier¶

Varying regularization in Multi-layer Perceptron¶

Feature discretization¶