An Internal Validity Index Based on Density-Involved Distance

Published in

IEEE Access(2019)

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TL;DR

A new robust distance measure, one into which density is incorporated, is designed to solve the problem, and an internal validity index based on this separation measure is then proposed, which can cope with both the spherical and non-spherical structure of clusters.

Abstract

It is crucial to evaluate the quality of clustering results in cluster analysis. Although many cluster validity indices (CVIs) have been proposed in the literature, they have some limitations when dealing with non-spherical datasets. One reason is that the measure of cluster separation does not consider the impact of outliers and neighborhood clusters. In this paper, a new robust distance measure, one into which density is incorporated, is designed to solve the problem, and an internal validity index based on this separation measure is then proposed. This index can cope with both the spherical and non-spherical structure of clusters. The experimental results indicate that the proposed index outperforms some classical CVIs.

Authors

Lianyu Hu

2 papers

Caiming Zhong

2 papers

References74 items

Ensemble Methods

A Novel Cluster Validity Index Based on Local Cores

Auto-weighted multi-view clustering via kernelized graph learning

Multiview Consensus Graph Clustering

A novel internal validity index based on the cluster centre and the nearest neighbour cluster

An Internal Validity Index Based on Density-Involved Distance

Published in

IEEE Access(2019)

External Links:

Generate Graph DownloadPDF

TL;DR

Abstract

Authors

Lianyu Hu

2 papers

Caiming Zhong

2 papers

References74 items

Ensemble Methods

A Novel Cluster Validity Index Based on Local Cores

Auto-weighted multi-view clustering via kernelized graph learning

Multiview Consensus Graph Clustering

A novel internal validity index based on the cluster centre and the nearest neighbour cluster

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Field of Study

Computer Science

Journal Information

Name

IEEE Access

Page

20991-21002

Volume

Venue Information

Name

IEEE Access

Type

journal

URL

http://www.ieee.org/publications_standards/publications/ieee_access.html