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Meta Analysis of Classification Algorithms for Pattern Recognition
November 1999 (vol. 21 no. 11)
pp. 1137-1144

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.

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Index Terms:
Data mining, meta analysis, logit model, multivariate statistics.
So Young Sohn, "Meta Analysis of Classification Algorithms for Pattern Recognition," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 11, pp. 1137-1144, Nov. 1999, doi:10.1109/34.809107
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