Construction of an optimal collective decision in cluster analysis on the basis of an averaged co-association matrix and cluster validity indices

Construction of an optimal collective decision in cluster analysis on the basis of an averaged co-association matrix and cluster validity indices Full article

Journal

Pattern Recognition and Image Analysis
ISSN: 1054-6618 , E-ISSN: 1555-6212

Output data

Year: 2017, Volume: 27, Number: 2, Pages: 153-165 Pages count : 13 DOI: 10.1134/S1054661816040040

Tags

classification; cluster analysis; cluster validity index; collective decision; ensemble of algorithms; latent classes; recognition model

Authors

Berikov V.B. ^1,2

Affiliations

1	Sobolev Institute of Mathematics, Siberian Branch, Russian Academy of Sciences, pr. Akademika Koptyuga 4, Novosibirsk, 630090, Russian Federation
2	Novosibirsk State University, Universitetskii pr. 2, Novosibirsk, 630090, Russian Federation

An ensemble clustering method is proposed that is based on a weight averaged co-association matrix. The ensemble includes various cluster analysis algorithms whose weights are calculated with the use of cluster validity indices. The properties of the ensemble are analyzed, a probabilistic model is described by which the relations between the characteristics of the ensemble and a quality estimate of a decision are determined, and a method is proposed for determining the optimal weights. The efficiency of the method is analyzed by statistical simulation. © 2017, Pleiades Publishing, Ltd.

Berikov V.B.
Construction of an optimal collective decision in cluster analysis on the basis of an averaged co-association matrix and cluster validity indices
Pattern Recognition and Image Analysis. 2017. V.27. N2. P.153-165. DOI: 10.1134/S1054661816040040 Scopus OpenAlex

Scopus:	2-s2.0-85020811618
OpenAlex:	W2625997883

DB	Citing
Scopus	7
OpenAlex	7