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Journal ArticleDOI

Validity index for crisp and fuzzy clusters

TLDR
A cluster validity index and its fuzzification is described, which can provide a measure of goodness of clustering on different partitions of a data set, and results demonstrating the superiority of the PBM-index in appropriately determining the number of clusters are provided.
About
This article is published in Pattern Recognition.The article was published on 2004-03-01. It has received 710 citations till now. The article focuses on the topics: Fuzzy clustering & Correlation clustering.

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Citations
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Proceedings ArticleDOI

K-means Clustering Algorithm with Improved Initial Center

Chen Zhang, +1 more
TL;DR: A new clustering method based on k-means that have avoided alternative randomness of initial center and does not require the user to be given in advance the number of cluster is presented.
Journal ArticleDOI

Underdetermined Convolutive Blind Source Separation via Time–Frequency Masking

TL;DR: Two algorithms are proposed, one for the estimation of the masks which are to be applied to the mixture in the TF domain for the separation of signals in the frequency domain, and the other for solving the permutation problem.
Journal ArticleDOI

A comprehensive survey of traditional, merge-split and evolutionary approaches proposed for determination of cluster number

TL;DR: Concepts and methods related to automatic cluster evolution from a theoretical perspective are introduced and methods reviewed that automatically determine the cluster number or cluster structure are reviewed in this study.
Journal ArticleDOI

A novel chaotic particle swarm optimization based fuzzy clustering algorithm

TL;DR: The CPSFC algorithm utilizes CPSO to search the fuzzy clustering model, exploiting the searching capability of fuzzy c-means (FCM) and avoiding its major limitation of getting stuck at locally optimal values.
Journal ArticleDOI

Mixture-model cluster analysis using information theoretical criteria

TL;DR: The relationship between the performance of information criteria and the type of measurement of clustering variables is analyzed and AIC3, BIC and ICL-BIC criteria are selected as the best candidates for model selection that refers to models with categorical, continuous and mixed type clusters variables.
References
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Book

Genetic algorithms in search, optimization, and machine learning

TL;DR: In this article, the authors present the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields, including computer programming and mathematics.

Genetic algorithms in search, optimization and machine learning

TL;DR: This book brings together the computer techniques, mathematical tools, and research results that will enable both students and practitioners to apply genetic algorithms to problems in many fields.
Book

Applied Multivariate Statistical Analysis

TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.
Journal ArticleDOI

Applied Multivariate Statistical Analysis.

TL;DR: In this article, the authors present an overview of the basic concepts of multivariate analysis, including matrix algebra and random vectors, as well as a strategy for analyzing multivariate models.