Cluster validation using legacy delineations

Mingqin Liu; Ashok Samal

doi:10.1016/S0262-8856(01)00089-0

Cluster validation using legacy delineations

Mingqin Liu, Ashok Samal

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Validation is an important aspect of clustering, but is often overlooked. The existing cluster validity measures are often inadequate for practical applications. Inability to incorporate existing domain knowledge is a primary deficiency. We have proposed a measure which models the domain knowledge in the form of existing delineations, often available from legacy. The effectiveness of the measure in a practical problem is demonstrated.

Original language	English (US)
Pages (from-to)	459-467
Number of pages	9
Journal	Image and Vision Computing
Volume	20
Issue number	7
DOIs	https://doi.org/10.1016/S0262-8856(01)00089-0
State	Published - May 1 2002

Keywords

Cluster validation
Clustering
Fuzzy clustering
Legacy datasets

ASJC Scopus subject areas

Signal Processing
Computer Vision and Pattern Recognition

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10.1016/S0262-8856(01)00089-0

Cite this

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abstract = "Validation is an important aspect of clustering, but is often overlooked. The existing cluster validity measures are often inadequate for practical applications. Inability to incorporate existing domain knowledge is a primary deficiency. We have proposed a measure which models the domain knowledge in the form of existing delineations, often available from legacy. The effectiveness of the measure in a practical problem is demonstrated.",

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KW - Fuzzy clustering

KW - Legacy datasets

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Cluster validation using legacy delineations

Abstract

Keywords

ASJC Scopus subject areas

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