Estimating the number of data clusters via the contrast statistic

Autor:	Oleg Gorshkov, Yuriy E. Lyakh, Yuriy Vihovanets, Vitaliy Gurianov
Rok vydání:	2012
Předmět:	Set (abstract data type) Uniform distribution (continuous) Dependency (UML) Ideal (set theory) business.industry Contrast (statistics) Pattern recognition Artificial intelligence Object (computer science) Cluster analysis business Statistic Mathematics
Zdroj:	Journal of Biomedical Science and Engineering. :95-99
ISSN:	1937-688X 1937-6871
DOI:	10.4236/jbise.2012.52012
Popis:	A new method (the Contrast statistic) for estimating the number of clusters in a set of data is proposed. The technique uses the output of self-organising map clustering algorithm, comparing the change in dependency of “Contrast” value upon clusters number to that expected under a uniform distribution. A simulation study shows that the Contrast statistic can be used successfully either, when variables describing the object in a multi-dimensional space are independent (ideal objects) or dependent (real biological objects).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::057514cc3a41affa63fe320e4b507a5d https://doi.org/10.4236/jbise.2012.52012 Zobrazit plný text záznamu