sklearn.metrics.pairwise.chi2_kernel¶
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sklearn.metrics.pairwise.chi2_kernel(X, Y=None, gamma=1.0)[source]¶ Computes the exponential chi-squared kernel 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)
- Yarray of shape (n_samples_Y, n_features)
- gammafloat, default=1.
Scaling parameter of the chi2 kernel.
- Returns
- kernel_matrixarray of shape (n_samples_X, n_samples_Y)
See also
additive_chi2_kernelThe additive version of this kernel
sklearn.kernel_approximation.AdditiveChi2SamplerA Fourier approximation to the additive version of this kernel.
References
Zhang, J. and Marszalek, M. and Lazebnik, S. and Schmid, C. Local features and kernels for classification of texture and object categories: A comprehensive study International Journal of Computer Vision 2007 https://research.microsoft.com/en-us/um/people/manik/projects/trade-off/papers/ZhangIJCV06.pdf