kernel_metrics#

sklearn.metrics.pairwise.kernel_metrics()[source]#

Valid metrics for pairwise_kernels.

This function simply returns the valid pairwise distance metrics. It exists, however, to allow for a verbose description of the mapping for each of the valid strings.

The valid distance metrics, and the function they map to, are:

metric	Function
‘additive_chi2’	sklearn.pairwise.additive_chi2_kernel
‘chi2’	sklearn.pairwise.chi2_kernel
‘linear’	sklearn.pairwise.linear_kernel
‘poly’	sklearn.pairwise.polynomial_kernel
‘polynomial’	sklearn.pairwise.polynomial_kernel
‘rbf’	sklearn.pairwise.rbf_kernel
‘laplacian’	sklearn.pairwise.laplacian_kernel
‘sigmoid’	sklearn.pairwise.sigmoid_kernel
‘cosine’	sklearn.pairwise.cosine_similarity