KL_divergence: Symmetrised Kullback - Leibler divergence (KL-Divergence)

In xinghuq/DA: Discriminant Analysis for Evolutionary Inference

Description

This function calculates Symmetrised Kullback - Leibler divergence (KL-Divergence) between each class. Designed for KLFDA.

Usage

KL_divergence(obj)

Arguments

obj	The KLFDA object. Users can mdify it to adapt your own purpose.

Value

Returns a symmetrised version of the KL divergence between each pair of class

Note

This function is useful for extimating the loss between reduced features and the original features. It has been adopted in TSNE to determine its projection performance.

Author(s)

[e-mail]

References

Van Erven, T., & Harremos, P. (2014). Renyi divergence and Kullback-Leibler divergence. IEEE Transactions on Information Theory, 60(7), 3797-3820.

Pierre Enel (2019). Kernel Fisher Discriminant Analysis (https://www.github.com/p-enel/MatlabKFDA), GitHub.

xinghuq/DA documentation built on July 11, 2021, 8:49 a.m.