# sklearn.metrics.pairwise.chi2_kernel¶

sklearn.metrics.pairwise.chi2_kernel(X, Y=None, gamma=1.0)[source]

Compute the exponential chi-squared kernel between X and Y.

The chi-squared kernel is computed between each pair of rows in X and Y. X and Y have to be non-negative. This kernel is most commonly applied to histograms.

The chi-squared kernel is given by:

k(x, y) = exp(-gamma Sum [(x - y)^2 / (x + y)])


It can be interpreted as a weighted difference per entry.

Read more in the User Guide.

Parameters:
Xarray-like of shape (n_samples_X, n_features)

A feature array.

Yndarray of shape (n_samples_Y, n_features), default=None

An optional second feature array. If None, uses Y=X.

gammafloat, default=1

Scaling parameter of the chi2 kernel.

Returns:
kernel_matrixndarray of shape (n_samples_X, n_samples_Y)

The kernel matrix.

additive_chi2_kernel
sklearn.kernel_approximation.AdditiveChi2Sampler