Large Margin Distribution Machine Recursive Feature Elimination

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Abstract

—In order to eliminate irrelevant features for classification, we propose a novel feature selection algorithm called Large Margin Distribution Machine Recursive Feature Elimination (LDM-RFE). LDM-RFE uses the latest support vector based classification algorithm Large Margin Distribution Machine (LDM) to evaluate all the features of samples, and then generates a ranked feature list during the procedure of Recursive Feature Elimination (RFE). In the experiment section, we report
promising results obtained by LDM-RFE in comparison with several common feature selection algorithms on five UCI benchmark datasets.
Original languageEnglish
Title of host publicationThe 2017 4th International Conference on Systems and Informatics (ICSAI 2017)
PublisherIEEE Press
Pages1427-1432
Number of pages6
ISBN (Print)978-1-5386-1106-7
Publication statusPublished - 2017
EventThe 2017 4th International Conference on Systems and Informatics - Hangzhou Zhejiang, China
Duration: 11 Nov 201713 Nov 2017

Conference

ConferenceThe 2017 4th International Conference on Systems and Informatics
Abbreviated titleICSAI 2017
CountryChina
CityHangzhou Zhejiang
Period11/11/1713/11/17

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Keywords

  • large margin distribution machine
  • recursive feature elimination
  • classification

Cite this

Ou, G., Wang, Y., Pang, W., & Coghill, G. M. (2017). Large Margin Distribution Machine Recursive Feature Elimination. In The 2017 4th International Conference on Systems and Informatics (ICSAI 2017) (pp. 1427-1432). IEEE Press.