sklearn.metrics.pairwise.additive_chi2_kernel(X, Y=None)
[source]
Computes the additive chi-squared kernel between observations in 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) = -Sum [(x - y)^2 / (x + y)]
It can be interpreted as a weighted difference per entry.
Read more in the User Guide.
Parameters: |
X : array-like of shape (n_samples_X, n_features) Y : array of shape (n_samples_Y, n_features) |
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Returns: |
kernel_matrix : array of shape (n_samples_X, n_samples_Y) |
See also
chi2_kernel
sklearn.kernel_approximation.AdditiveChi2Sampler
As the negative of a distance, this kernel is only conditionally positive definite.
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Licensed under the 3-clause BSD License.
http://scikit-learn.org/stable/modules/generated/sklearn.metrics.pairwise.additive_chi2_kernel.html