A Feature Weighting Approach to Building Classification Models by Interactive Clustering

Liping Jing, Joshua Huang, Michael K. Ng, Hongqiang Rong

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

3 Citations (Scopus)

Abstract

In using a classified data set to test clustering algorithms, the data points in a class are considered as one cluster (or more than one) in space. In this paper we adopt this principle to build classification models through interactively clustering a training data set to construct a tree of clusters. The leaf clusters of the tree are selected as decision clusters to classify new data based on a distance function. We consider the feature weights in calculating the distances between a new object and the center of a decision cluster. The new algorithm, W-k-means, is used to automatically calculate the feature weights from the training data. The Fastmap technique is used to handle outliers in selecting decision clusters. This step increases the stability of the classifier. Experimental results on public domain data sets have shown that the models built using this clustering approach outperformed some popular classification algorithms.

Original languageEnglish
Title of host publicationModeling Decisions for Artificial Intelligence
Subtitle of host publicationFirst International Conference, MDAI 2004, Barcelona, Spain, August 2-4, 2004, Proceedings
EditorsVicenc Torra, Yasuo Narukawa
PublisherSpringer Berlin Heidelberg
Pages284-294
Number of pages11
Edition1st
ISBN (Electronic)9783540277743
ISBN (Print)9783540225553
DOIs
Publication statusPublished - 16 Jul 2004
Event1st International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2004 - Barcelona, Catalonia, Spain
Duration: 2 Aug 20044 Aug 2004
https://link.springer.com/book/10.1007/b99254

Publication series

NameLecture Notes in Computer Science
Volume3131
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameLecture Notes in Artificial Intelligence
ISSN (Print)2945-9133
ISSN (Electronic)2945-9141
NameMDAI: International Conference on Modeling Decisions for Artificial Intelligence

Conference

Conference1st International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2004
Country/TerritorySpain
CityBarcelona, Catalonia
Period2/08/044/08/04
Internet address

Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

User-Defined Keywords

  • Classification
  • Clustering
  • Data mining
  • DCC
  • Feature weight

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