Unsupervised learning algorithm for fuzzy clustering.

Kiichi Urahama

Unsupervised learning algorithm for fuzzy clustering.

Kiichi Urahama

Visual Communication Design

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

2 Citations (Scopus)

Abstract

An adaptive algorithm is presented for fuzzy clustering of data. Partitioning is fuzzified by addition of an entropy term to objective functions. The proposed method produces more convex membership functions than those given by the fuzzy c- means algorithm.

Original language	English
Pages (from-to)	390-391
Number of pages	2
Journal	IEICE Transactions on Information and Systems
Volume	E76-D
Issue number	3
Publication status	Published - Mar 1 1993

All Science Journal Classification (ASJC) codes

Software
Hardware and Architecture
Computer Vision and Pattern Recognition
Electrical and Electronic Engineering
Artificial Intelligence

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title = "Unsupervised learning algorithm for fuzzy clustering.",

abstract = "An adaptive algorithm is presented for fuzzy clustering of data. Partitioning is fuzzified by addition of an entropy term to objective functions. The proposed method produces more convex membership functions than those given by the fuzzy c- means algorithm.",

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year = "1993",

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Unsupervised learning algorithm for fuzzy clustering.

Abstract

All Science Journal Classification (ASJC) codes

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