Meta analysis of classification algorithms for pattern recognition

So Young Sohn

doi:10.1109/34.809107

Meta analysis of classification algorithms for pattern recognition

So Young Sohn

Department of Industrial Engineering

Research output: Contribution to journal › Article › peer-review

86 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 language	English
Pages (from-to)	1137-1144
Number of pages	8
Journal	IEEE transactions on pattern analysis and machine intelligence
Volume	21
Issue number	11
DOIs	https://doi.org/10.1109/34.809107
Publication status	Published - 1999

Bibliographical note

Funding Information:
This work was partly supported by the Yonsei University Research Fund of 1997 and by grant no, 1999-1-303-005-3 from the Interdisciplinary Research Program of the KOSEF..

All Science Journal Classification (ASJC) codes

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

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Meta analysis of classification algorithms for pattern recognition

Abstract

Bibliographical note

All Science Journal Classification (ASJC) codes

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