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Scoring Feature Sub...
Scoring Feature Subsets for Separation power in Supervised Bayes Classification
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- Pavlenko, Tatjana (författare)
- Mittuniversitetet,Institutionen för teknik, fysik och matematik (-2008),Mid Sweden University
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- Fridén, Håkan (författare)
- Mittuniversitetet,Institutionen för teknik, fysik och matematik (-2008)
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(creator_code:org_t)
- Berlin : Springer, 2006
- 2006
- Engelska.
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Ingår i: Advances in Intelligent and Soft Computing. - Berlin : Springer. - 1867-5662 .- 1867-5670. - 9783540347767 ; 37, s. 383-391, s. 383-391
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- We present a method for evaluating the discriminative power of compact feature combinations (blocks) using the distance-based scoring measure, yielding an algorithm for selecting feature blocks that significantly contribute to the outcome variation. To estimate classification performance with subset selection in a high dimensional framework we jointly evaluate both stages of the process: selection of significantly relevant blocks and classification. Classification power and performance properties of the classifier with the proposed subset selection technique has been studied on several simulation models and confirms the benefit of this approach.
Ämnesord
- NATURVETENSKAP -- Matematik (hsv//swe)
- NATURAL SCIENCES -- Mathematics (hsv//eng)
Nyckelord
- multivariate statistics
- classification
- MATHEMATICS
- MATEMATIK
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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