APPLICATION OF PROBABILISTIC SETS TO FUZZY CLUSTERING.

Witold Pedrycz; Kaoru Hirota

APPLICATION OF PROBABILISTIC SETS TO FUZZY CLUSTERING.

Witold Pedrycz^*
, Kaoru Hirota

^*Corresponding author for this work

School of Automation

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

2 Citations (Scopus)

Abstract

Characterization of fuzzy clustering algorithms is dealt with using the concept of probabilistic sets and their subjective entropy. Clustering techniques with objective performance-index criterion-functions are discussed. Several indices characterized by subjective entropy, including indices expressing the degree of interaction between clusters, are proposed. The utility of these indices is illustrated by a simulation method using Iris data and also handwritten-character data.

Original language	English
Title of host publication	Anal of Fuzzy Inf
Publisher	CRC Press Inc
Pages	169-181
Number of pages	13
ISBN (Print)	0849362989
Publication status	Published - 1987

Cite this

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title = "APPLICATION OF PROBABILISTIC SETS TO FUZZY CLUSTERING.",

abstract = "Characterization of fuzzy clustering algorithms is dealt with using the concept of probabilistic sets and their subjective entropy. Clustering techniques with objective performance-index criterion-functions are discussed. Several indices characterized by subjective entropy, including indices expressing the degree of interaction between clusters, are proposed. The utility of these indices is illustrated by a simulation method using Iris data and also handwritten-character data.",

author = "Witold Pedrycz and Kaoru Hirota",

year = "1987",

language = "English",

isbn = "0849362989",

pages = "169--181",

booktitle = "Anal of Fuzzy Inf",

publisher = "CRC Press Inc",

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TY - CHAP

T1 - APPLICATION OF PROBABILISTIC SETS TO FUZZY CLUSTERING.

AU - Pedrycz, Witold

AU - Hirota, Kaoru

PY - 1987

Y1 - 1987

N2 - Characterization of fuzzy clustering algorithms is dealt with using the concept of probabilistic sets and their subjective entropy. Clustering techniques with objective performance-index criterion-functions are discussed. Several indices characterized by subjective entropy, including indices expressing the degree of interaction between clusters, are proposed. The utility of these indices is illustrated by a simulation method using Iris data and also handwritten-character data.

AB - Characterization of fuzzy clustering algorithms is dealt with using the concept of probabilistic sets and their subjective entropy. Clustering techniques with objective performance-index criterion-functions are discussed. Several indices characterized by subjective entropy, including indices expressing the degree of interaction between clusters, are proposed. The utility of these indices is illustrated by a simulation method using Iris data and also handwritten-character data.

UR - https://www.scopus.com/pages/publications/0023540230

M3 - Chapter

AN - SCOPUS:0023540230

SN - 0849362989

SP - 169

EP - 181

BT - Anal of Fuzzy Inf

PB - CRC Press Inc

ER -

APPLICATION OF PROBABILISTIC SETS TO FUZZY CLUSTERING.

Abstract

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