INTERPRETING THE KOHONEN SELF-ORGANIZING FEATURE MAP USING CONTIGUITY-CONSTRAINED CLUSTERING

被引：77

作者：

MURTAGH, F ^{[1
]}

机构：

[1] EUROPEAN SPACE AGCY,DEPT SPACE SCI,DIV ASTROPHYS,F-75738 PARIS 15,FRANCE

来源：

PATTERN RECOGNITION LETTERS | 1995年 / 16卷 / 04期

关键词：

CLUSTER ANALYSIS; NEURAL NETWORKS; HIERARCHICAL CLUSTERING; REGIONALIZATION; SEGMENTATION; DATA ANALYSIS; IMAGE PROCESSING;

D O I：

10.1016/0167-8655(94)00113-H

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

An interpretation phase is proposed, to complement usage of the Kohonen self-organizing feature map (SOFM) method. This segments the SOFM output, using an agglomerative contiguity-constrained clustering method. We discuss why such a clustering method, which respects contiguity information, should be used. The contiguity-constrained clustering method implemented uses array operations as far as possible, and is thus quite efficient. An application to an astronomical catalog of about a quarter million objects is presented.

引用

页码：399 / 408

页数：10

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