Ensemble multi-label text categorization based on rotation forest and latent semantic indexing

作者：

Highlights：

• A novel ensemble multi-label classification method for text categorization.

• Combination of both Rotation Forest paradigm and Latent Semantic Indexing.

• This combination enhances both diversity and accuracy in the ensemble.

• Experiments on 14 real text categorization multi-label data sets.

摘要

•A novel ensemble multi-label classification method for text categorization.•Combination of both Rotation Forest paradigm and Latent Semantic Indexing.•This combination enhances both diversity and accuracy in the ensemble.•Experiments on 14 real text categorization multi-label data sets.

论文关键词：Multi-label classification,Text categorization,Ensemble learning,Rotation forest,Content analysis and indexing

论文评审过程：Received 27 October 2015, Revised 22 March 2016, Accepted 23 March 2016, Available online 24 March 2016, Version of Record 31 March 2016.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.03.041