sklearn.datasets.make_hastie_10_2¶
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sklearn.datasets.make_hastie_10_2(n_samples=12000, *, random_state=None)[source]¶ Generates data for binary classification used in Hastie et al. 2009, Example 10.2.
The ten features are standard independent Gaussian and the target
yis defined by:y[i] = 1 if np.sum(X[i] ** 2) > 9.34 else -1
Read more in the User Guide.
- Parameters
- n_samplesint, optional (default=12000)
The number of samples.
- random_stateint, RandomState instance, default=None
Determines random number generation for dataset creation. Pass an int for reproducible output across multiple function calls. See Glossary.
- Returns
- Xarray of shape [n_samples, 10]
The input samples.
- yarray of shape [n_samples]
The output values.
See also
make_gaussian_quantilesa generalization of this dataset approach
References
- 1
T. Hastie, R. Tibshirani and J. Friedman, “Elements of Statistical Learning Ed. 2”, Springer, 2009.
