sklearn.datasets
.make_s_curve¶
- sklearn.datasets.make_s_curve(n_samples=100, *, noise=0.0, random_state=None)[source]¶
Generate an S curve dataset.
Read more in the User Guide.
- Parameters:
- n_samplesint, default=100
The number of sample points on the S curve.
- noisefloat, default=0.0
The standard deviation of the gaussian noise.
- random_stateint, RandomState instance or None, default=None
Determines random number generation for dataset creation. Pass an int for reproducible output across multiple function calls. See Glossary.
- Returns:
- Xndarray of shape (n_samples, 3)
The points.
- tndarray 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
¶
Comparison of Manifold Learning methods
Comparison of Manifold Learning methods
t-SNE: The effect of various perplexity values on the shape
t-SNE: The effect of various perplexity values on the shape