treeple.datasets.make_quadratic_classification

treeple.datasets.make_quadratic_classification(n_samples, n_features, noise=False, seed=None)

Simulate classification data from a quadratic model.

This is a form of the simulation used in [1].

Parameters:

n_samplesint

The number of samples to generate.

n_featuresint

The number of dimensions in the dataset.

noisebool, optional

Whether or not to add noise, by default False.

seedint, optional

Random seed, by default None.

Returns:

xarray_like, shape (2 * n_samples, n_features)

Data array.

varray_like, shape (2 * n_samples,)

Target array of 1’s and 0’s.

References

[1]

Sambit Panda, Cencheng Shen, and Joshua T Vogelstein. Learning interpretable characteristic kernels via decision forests. arXiv preprint arXiv:1812.00029, 2018.