- sklearn.metrics.pairwise.chi2_kernel(X, Y=None, gamma=1.0)¶
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.
X : array-like of shape (n_samples_X, n_features)
Y : array of shape (n_samples_Y, n_features)
gamma : float, default=1.
Scaling parameter of the chi2 kernel.
kernel_matrix : array of shape (n_samples_X, n_samples_Y)
- 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 http://eprints.pascal-network.org/archive/00002309/01/Zhang06-IJCV.pdf