Large Margin Distribution Machine Recursive Feature Elimination

Ge Ou, Yan Wang, Wei Pang, George MacLeod Coghill

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

In order to eliminate irrelevant features forclassification, we propose a novel feature selection algorithmcalled Large Margin Distribution Machine Recursive FeatureElimination (LDM-RFE). LDM-RFE uses the latest supportvector based classification algorithm Large Margin DistributionMachine (LDM) to evaluate all the features of samples, and thengenerates a ranked feature list during the procedure of RecursiveFeature Elimination (RFE). In the experiment section, we reportpromising results obtained by LDM-RFE in comparison withseveral common feature selection algorithms on five UCIbenchmark datasets.
Original languageEnglish
Title of host publication2017 4th International Conference on Systems and Informatics (ICSAI)
PublisherIEEE
Pages1518-1523
Number of pages6
ISBN (Electronic)9781538611074
DOIs
Publication statusPublished - 8 Jan 2018

Keywords

  • large margin distribution machine
  • recursive feature elimination
  • classification

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  • Cite this

    Ou, G., Wang, Y., Pang, W., & Coghill, G. M. (2018). Large Margin Distribution Machine Recursive Feature Elimination. In 2017 4th International Conference on Systems and Informatics (ICSAI) (pp. 1518-1523). IEEE. https://doi.org/10.1109/ICSAI.2017.8248525