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

Read more in the User Guide.

Returns:
kernel_metricsdict

Returns valid metrics for pairwise_kernels.