A Machine learning algorithm based on supervised clustering and classification

Nong Ye, Xiangyang Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

In this paper a novel data mining technique – Clustering and Classification Algorithm-Supervised (CCA-S)1 is introduced. CCA-S supports incremental learning and non-hierarchical clustering, and is scalable for processing large data sets. CCA-S incorporates the class information in making clustering decisions, and uses the resulting clusters to classify new data records. We apply and test CCA-S on several common data sets for classification problems. The testing results show that the classification performance of CCAS is comparable to the other classification algorithms such as decision trees, artificial neural networks and discriminant analysis.

Original languageEnglish (US)
Title of host publicationActive Media Technology - 6th International Computer Science Conference, AMT 2001, Proceedings
EditorsJiming Liu, Pong C. Yuen, Chun-hung Li, Joseph Ng, Toru Ishida
PublisherSpringer Verlag
Pages327-334
Number of pages8
ISBN (Electronic)9783540430353
DOIs
StatePublished - Jan 1 2001
Event6th International Computer Science Conference on Active Media Technology, AMT 2001 - Hong Kong, China
Duration: Dec 18 2001Dec 20 2001

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2252
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Computer Science Conference on Active Media Technology, AMT 2001
Country/TerritoryChina
CityHong Kong
Period12/18/0112/20/01

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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