Why Does Output Normalization Create Problems in Multiple Classifier Systems?

@inproceedings{Altinay2002WhyDO,
  title={Why Does Output Normalization Create Problems in Multiple Classifier Systems?},
  author={Hakan Altinçay and M{\"u}beccel Demirekler},
  booktitle={ICPR},
  year={2002}
}
Combination of classifiers is a promising direction for obtaining better classification systems. However, the outputs of different classifiers may have different scales and hence the classifier outputs are incomparable. Incomparability of the classifier output scores is a major problem in the combination of different classification systems. In order to avoid this problem, the measurement level classifier outputs are generally normalized. However, recent studies have proven that output… CONTINUE READING

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On Combining Classifiers

IEEE Trans. Pattern Anal. Mach. Intell. • 1998
View 1 Excerpt

Information combination operators for data fusion: a comparative review with classification

IEEE Trans. Systems, Man, and Cybernetics, Part A • 1996
View 1 Excerpt

Person identification using multiple cues

IEEE Transactions on Pattern Analysis and Machine Intelligence • 1995
View 1 Excerpt

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