eprintid: 1372
rev_number: 12
eprint_status: archive
userid: 2
dir: disk0/00/00/13/72
datestamp: 2015-02-20 14:28:05
lastmod: 2017-02-08 12:21:32
status_changed: 2015-04-27 12:10:47
type: article
metadata_visibility: show
creators_name: Cha, Sung-Hyuk
creators_id: scha@pace.edu
corp_creators: omputer Science Department, Pace University, 861  Bedford rd, Pleasantville, NY 10570 USA
title: Comprehensive Survey on Distance/Similarity 
Measures between Probability Density Functions
ispublished: pub
subjects: SS
divisions: EPOS-P
full_text_status: none
keywords: Distance,  Histogram,  Probability  Density  Function, 
Similarity
abstract: 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.
date: 2007
date_type: published
publication: International Journal of Mathematical models and Methods in Applied Sciences
volume: 1
number: 4
publisher: World Scientific Publishing
pagerange: 300-307
refereed: TRUE
issn: 1793-6314
access_IS-EPOS: limited
owner: Publisher
citation:   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.