Weighted ensemble of algorithms for complex data clustering

被引：28

作者：

Berikov, Vladimir ^{[1
,2
]}

机构：

[1] Sobolev Inst Math, Novosibirsk 630090, Russia

[2] Novosibirsk State Univ, Novosibirsk 630090, Russia

来源：

PATTERN RECOGNITION LETTERS | 2014年 / 38卷

基金：

俄罗斯基础研究基金会;

关键词：

Clustering; Classification; Weighted clustering ensemble; Latent variable model; Classification error bound;

D O I：

10.1016/j.patrec.2013.11.012

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper considers a problem of clustering complex data composed from various structures. A collection of different algorithms is used for the analysis. The main idea is based on the assumption that each algorithm is "specialized" (as a rule, gives more accurate partition results) on particular types of structures. The degree of algorithm's "competence" is determined by usage of weights attributed to each pair of observations. Optimal weights are specified by the analysis of partial ensemble solutions with use of the proposed model of clustering ensemble. The efficiency of the suggested approach is demonstrated with Monte-Carlo modeling. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：99 / 106

页数：8

共 23 条

[1]

[Anonymous], MATH CLASSIFICATION

[2]

[Anonymous], ACM T KNOWL DISCOVER

[3]

[Anonymous], 2008, P 2008 SIAM INT C DA

[4]

Banerjee A, 2005, J MACH LEARN RES, V6, P1705

[5]

Berikov V, 2011, LECT NOTES COMPUT SC, V6713, P279, DOI 10.1007/978-3-642-21557-5_30

[6] Random forests [J].

Breiman, L .

MACHINE LEARNING, 2001, 45 (01) :5-32

[7]

Cussens J., 1993, Machine Learning: ECML-93. European Conference on Machine Learning Proceedings, P136

[8] Combining multiple clusterings using evidence accumulation [J].

Fred, ALN ;

Jain, AK .

IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2005, 27 (06) :835-850

[9] A clustering method based on boosting [J].

Frossyniotis, D ;

Likas, A ;

Stafylopatis, A .

PATTERN RECOGNITION LETTERS, 2004, 25 (06) :641-654

[10] Cluster ensembles [J].

Ghosh, Joydeep ;

Acharya, Ayan .

WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2011, 1 (04) :305-315

← 1 2 3 →