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Summary: MultiStage Cascading of Multiple Classifiers:
One Man's Noise is Another Man's Data
Cenk Kaynak CENK.KAYNAK@UNILEVER.COM
Ethem Alpaydin ALPAYDIN@BOUN.EDU.TR
Department of Computer Engineering, Bogazici University, Istanbul TR80815 Turkey
Abstract
For building implementable and industry
valuable classification solutions, machine
learning methods must focus not only on
accuracy but also on computational and space
complexity. We discuss a multistage method,
namely cascading, where there is a sequence of
classifiers ordered in terms of increasing
complexity and specificity such that early
classifiers are simple and general whereas later
ones are more complex and specific, being
localized on patterns rejected by the previous
classifiers. We present the technique and its
rationale and validate its use by comparing it
with the individual classifiers as well as the
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