Online group feature selection

Jing Wang, Zhong Qiu Zhao, Xuegang Hu, Yiu Ming Cheung, Meng Wang, Xindong Wu*

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

34 Citations (Scopus)


Online feature selection with dynamic features has become an active research area in recent years. However, in some real-world applications such as image analysis and email spam filtering, features may arrive by groups. Existing online feature selection methods evaluate features individually, while existing group feature selection methods cannot handle online processing. Motivated by this, we formulate the online group feature selection problem, and propose a novel selection approach for this problem. Our proposed approach consists of two stages: online intra-group selection and online inter-group selection. In the intra-group selection, we use spectral analysis to select discriminative features in each group when it arrives. In the inter-group selection, we use Lasso to select a globally optimal subset of features. This 2-stage procedure continues until there are no more features to come or some predefined stopping conditions are met. Extensive experiments conducted on benchmark and real-world data sets demonstrate that our proposed approach outperforms other state-of-the-art online feature selection methods.

Original languageEnglish
Title of host publicationIJCAI 2013 - Proceedings of the 23rd International Joint Conference on Artificial Intelligence
PublisherAAAI press
Number of pages7
ISBN (Print)9781577356332
Publication statusPublished - 2013
Event23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 - Beijing, China, Beijing, China
Duration: 3 Aug 20139 Aug 2013

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823


Conference23rd International Joint Conference on Artificial Intelligence, IJCAI 2013
Internet address

Scopus Subject Areas

  • Artificial Intelligence


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