Abstract

In this work, we deal with a relatively new statistical tool in machine learning: the estimation of the ratio of two probability densities, or density ratio estimation for short. As a side piece of research that gained its own traction, we also tackle the task of parameter selection in learning algorithms based on kernel methods.

Abstract

Stochastic Density Ratio Estimation and Its Application to Feature Selection / 4345 Igor Braga PDF