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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.
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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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Journal ArticleDOI

A novel cluster validity index based on augmented non-shared nearest neighbors

TL;DR: In this article , the authors proposed a new cluster validity index based on augmented non-shared nearest neighbors (ANCV), which is based on the following principles: (1) Within-cluster compactness can be measured by the distance between the pairs of data points with fewer shared nearest neighbors.
Journal Article

On Limiting Behavior of the PBM and the Fuzzified PBM Cluster Validity Index

TL;DR: In this paper, the limiting behavior of the PBM and the fuzzified PBM (PBMF) clustering validity indices are investigated and a punishing function is introduced to avoid the indetermination due to monotonicity of thePBM index.
Proceedings ArticleDOI

A new cluster validity index for type-2 fuzzy c-means algorithm

TL;DR: A new cluster validity index for the type-2 FCM called SM-index is proposed, based on the cluster fuzzy degree of FCM fuzzy set and the existing cluster validity indices that are suitable for FCM clustering algorithm.
Proceedings ArticleDOI

Approaches to cluster validity index via mahalanobis metric

TL;DR: New cluster validity index IRY is proposed via using the Mahalanobis metric for the validation of partitions of object data produced by DBCAMM algorithm, and the results show the superior effectiveness and reliability of the proposed index in comparison to the results of other clusters validity index for FCM clustering algorithm.
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.