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Ensemble Pruning via DC Programming

Akyuz, S, Windeatt, T and Smith, R Ensemble Pruning via DC Programming

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Abstract

Ensemble learning is a method of combining learners, however the ensemble sizes are sometimes unnecessarily large which causes extra memory usage and decrease in effectiveness. Error Correcting Output Code (ECOC) is one of the well known ensemble techniques for multiclass classification which combines the outputs of binary base learners to predict the classes for multiclass data. We formulate ECOC for ensemble selection problem by using difference of convex functions (dc) programming and zero norm approximation to cardinality constraint. Experiments show that it outperforms the standard ECOC.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Authors :
NameEmailORCID
Akyuz, Ss.akyuz@surrey.ac.ukUNSPECIFIED
Windeatt, TUNSPECIFIEDUNSPECIFIED
Smith, RUNSPECIFIEDUNSPECIFIED
Depositing User : Symplectic Elements
Date Deposited : 17 May 2017 12:34
Last Modified : 17 May 2017 12:34
URI: http://epubs.surrey.ac.uk/id/eprint/835891

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