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ICPR
2006
IEEE

A 'No Panacea Theorem' for Multiple Classifier Combination

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A 'No Panacea Theorem' for Multiple Classifier Combination
We introduce the `No Panacea Theorem' for classifier combination in the two-classifier, two-class case. It states that if the combination function is continuous and diverse, there exists a situation in which the combination algorithm will always give very bad performance. Thus, there is no optimal algorithm, suitable in all situations. From this theorem, we see that the probability density functions (pdf's) play an important role in the performance of combination algorithms, so studying the pdf's becomes the first step in finding a good algorithm.
Robert I. Damper, Roland Hu
Added 09 Nov 2009
Updated 09 Nov 2009
Type Conference
Year 2006
Where ICPR
Authors Robert I. Damper, Roland Hu
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