Optimal linear regression on classifier outputs | Zendy

Yann Guermeur | Zendy; Florence d’Alché–Buc | Zendy; Patrick Gallinari | Zendy

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Optimal linear regression on classifier outputs

Author(s) -

Yann Guermeur,

Florence d’Alché–Buc,

Patrick Gallinari

Publication year - 1997

Publication title -

lecture notes in computer science

Language(s) - English

Resource type - Book series

SCImago Journal Rank - 0.249

H-Index - 400

eISSN - 1611-3349

pISSN - 0302-9743

ISBN - 3-540-63631-5

DOI - 10.1007/bfb0020201

Subject(s) - computer science , classifier (uml) , artificial intelligence , machine learning , task (project management) , linear regression , pattern recognition (psychology) , regression , statistics , mathematics , management , economics

International audienceWe consider the combination of the outputs of several classifiers trained independently for the same discrimination task. We introduce new results which provide optimal solutions in the case of linear combinations. We compare our solutions to existing ensemble methods and characterize situations where our approach should be preferred

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