The fuzzy hierarchical cross-clustering algorithm. Improvements and comparative study

被引：15

作者：

Pop, HF ^{[1
]}

Sarbu, C ^{[1
]}

机构：

[1] UNIV BABES BOLYAI,FAC CHEM,RO-3400 CLUJ NAPOCA,ROMANIA

来源：

JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES | 1997年 / 37卷 / 03期

关键词：

fuzzy hierarchical cross-classification; pattern recognition; solvents;

D O I：

10.1021/ci960148v

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

The aim of this paper is to introduce a way to improve the behavior of the Fuzzy Hierarchical Cross-Clustering Algorithm. The Simultaneous Fuzzy n-Means Algorithm produces fuzzy n-partitions of objects and characteristics, but it does not offer a modality to associate each fuzzy set of objects to a fuzzy set of characteristics. Based on our previous experience we are able to propose such an association. In the second part of the paper we will study the behavior of the Fuzzy Hierarchical Cross-Clustering Algorithm using both the original and the Improved Simultaneous Fuzzy n-Means Algorithm.

引用

页码：510 / 516

页数：7

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