A hybrid classification algorithm by subspace partitioning through semi-supervised decision tree

作者：

Highlights：

• Propose the semi-supervised split criterion for decision trees.

• Combine the semi-supervised decision tree as subspace partitioning with other classifiers.

• Experiments on several datasets showed that the proposed method outperforms the existing ones.

摘要

Highlights•Propose the semi-supervised split criterion for decision trees.•Combine the semi-supervised decision tree as subspace partitioning with other classifiers.•Experiments on several datasets showed that the proposed method outperforms the existing ones.

论文关键词：Decision tree,Semi-supervised decision tree,Inhomogeneous measure,Subspace partitioning

论文评审过程：Received 7 December 2015, Revised 21 April 2016, Accepted 25 April 2016, Available online 17 May 2016, Version of Record 2 June 2016.

论文官网地址：https://doi.org/10.1016/j.patcog.2016.04.016