relation: https://episodesplatform.eu/eprints/1372/
title: Comprehensive Survey on Distance/Similarity  Measures between Probability Density Functions
creator: Cha, Sung-Hyuk
subject: Method and procesing
description: Distance or similarity measures are essential to solve  many pattern recognition problems such as classification, clustering, and retrieval problems. Various distance/similarity measures that are applicable to compare two probability density functions, pdf in short, are  reviewed  and  categorized  in  both  syntactic  and  semantic relationships. A correlation coefficient and a hierarchical clustering technique  are  adopted  to  reveal  similarities  among numerous distance/similarity measures.
publisher: World Scientific Publishing
date: 2007
type: Article
type: PeerReviewed
identifier:   Cha, Sung-Hyuk  (2007) Comprehensive Survey on Distance/Similarity Measures between Probability Density Functions.  International Journal of Mathematical models and Methods in Applied Sciences, 1 (4).  pp. 300-307.