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sklearn.datasets.make_s_curve

sklearn.datasets.make_s_curve(n_samples=100, noise=0.0, random_state=None)

Generate an S curve dataset.

Read more in the User Guide.

Parameters:

n_samples : int, optional (default=100)

The number of sample points on the S curve.

noise : float, optional (default=0.0)

The standard deviation of the gaussian noise.

random_state : int, RandomState instance or None (default)

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

Returns:

X : array of shape [n_samples, 3]

The points.

t : array of shape [n_samples]

The univariate position of the sample according to the main dimension of the points in the manifold.

Examples using sklearn.datasets.make_s_curve

t-SNE: The effect of various perplexity values on the shape

Comparison of Manifold Learning methods