An empirical comparison of nine pattern classifiers

Quoc Long Tran, Kar Ann Toh, Dipti Srinivasan, Kok Leong Wong, Shaun Qiu Cen Low

Research output: Contribution to journalArticle

15 Citations (Scopus)

Abstract

There are many learning algorithms available in the field of pattern classification and people are still discovering new algorithms that they hope will work better. Any new learning algorithm, beside its theoretical foundation, needs to be justified in many aspects including accuracy and efficiency when applied to real life problems. In this paper, we report the empirical comparison of a recent algorithm RM, its new extensions and three classical classifiers in different aspects including classification accuracy, computational time and storage requirement. The comparison is performed in a standardized way and we believe that this would give a good insight into the algorithm RM and its extension. The experiments also show that nominal attributes do have an impact on the performance of those compared learning algorithms.

Original languageEnglish
Pages (from-to)1079-1091
Number of pages13
JournalIEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Volume35
Issue number5
DOIs
Publication statusPublished - 2005 Oct 1

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Learning algorithms
Classifiers
Pattern recognition
Experiments

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Artificial Intelligence
  • Human-Computer Interaction

Cite this

Tran, Quoc Long ; Toh, Kar Ann ; Srinivasan, Dipti ; Wong, Kok Leong ; Low, Shaun Qiu Cen. / An empirical comparison of nine pattern classifiers. In: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics. 2005 ; Vol. 35, No. 5. pp. 1079-1091.
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An empirical comparison of nine pattern classifiers. / Tran, Quoc Long; Toh, Kar Ann; Srinivasan, Dipti; Wong, Kok Leong; Low, Shaun Qiu Cen.

In: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, Vol. 35, No. 5, 01.10.2005, p. 1079-1091.

Research output: Contribution to journalArticle

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