Title :
Estimation of density ratio and its application to design a measure of dependence
Author :
Seth, Sohan ; Príncipe, José C.
Author_Institution :
Electr. & Comput. Eng., Univ. of Florida, Gainesville, FL, USA
Abstract :
In this paper we propose a new approach to estimate the ratio of two probability density functions. The proposed approach is inspired by the kernel based function approximation technique. We apply this estimator to derive an estimator of mutual information and show that this estimator can be successfully used to detect dependence between two random variables.
Keywords :
learning (artificial intelligence); probability; density ratio estimation; dependence measure; function approximation technique; mutual information; probability density functions; random variables; Application software; Density functional theory; Density measurement; Design engineering; Electric variables measurement; Gain measurement; Kernel; Mutual information; Probability density function; Random variables;
Conference_Titel :
Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on
Conference_Location :
Grenoble
Print_ISBN :
978-1-4244-4947-7
Electronic_ISBN :
978-1-4244-4948-4
DOI :
10.1109/MLSP.2009.5306226
