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_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.
Returns:	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

Classifier comparison

Comparing different clustering algorithms on toy datasets

Varying regularization in Multi-layer Perceptron

Compare Stochastic learning strategies for MLPClassifier