An asymptotic analysis of some expert fusion methods

Dechang Chen*, Xiuzhen Cheng

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


We study the asymptotic behavior of three classifier combination methods for two-class classification: Average, median, and majority vote. Assuming that the estimates of the posterior probability given by individual classifiers constitute a sample from a distribution, we show that as the number of individual classifiers becomes large, median and majority will produce the same result but average may yield a completely different decision if the distribution is not symmetric.

Original languageEnglish
Pages (from-to)901-904
Number of pages4
JournalPattern Recognition Letters
Issue number8
StatePublished - Jun 2001
Externally publishedYes


  • Classifier combination
  • Error rate
  • Majority vote
  • Order statistics


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