Meta analysis of classification algorithms for pattern recognition

Research output: Contribution to journalArticle

78 Citations (Scopus)

Abstract

Various classification algorithms became available due to a surge of interdisciplinary research interests in the areas of data mining and knowledge discovery. We develop a statistical meta-model which compares the classification performances of several algorithms in terms of data characteristics. This empirical model is expected to aid decision making processes of finding the best classification tool in the sense of providing the minimum classification error among alternatives.

Original languageEnglish
Pages (from-to)1137-1144
Number of pages8
JournalIEEE transactions on pattern analysis and machine intelligence
Volume21
Issue number11
DOIs
Publication statusPublished - 1999 Dec 1

Fingerprint

Classification Algorithm
Pattern Recognition
Pattern recognition
Data mining
Empirical Model
Surge
Knowledge Discovery
Metamodel
Data Mining
Decision Making
Decision making
Alternatives

All Science Journal Classification (ASJC) codes

  • Software
  • Computer Vision and Pattern Recognition
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

Cite this

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Meta analysis of classification algorithms for pattern recognition. / Sohn, So Young.

In: IEEE transactions on pattern analysis and machine intelligence, Vol. 21, No. 11, 01.12.1999, p. 1137-1144.

Research output: Contribution to journalArticle

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