Software defect prediction using a cost sensitive decision forest and voting, and a potential solution to the class imbalance problem

作者：

Highlights：

• SDP is short for Software Defect Prediction.

• We show that there is not a clear winner in the studied existing methods for SDP⁎.

• A cost-sensitive decision forest and voting technique are proposed.

• The superiority of the proposed techniques is shown.

• A proposed framework for the forest algorithm for handling class imbalance.

摘要

Author-Highlights•SDP is short for Software Defect Prediction.•We show that there is not a clear winner in the studied existing methods for SDP⁎.•A cost-sensitive decision forest and voting technique are proposed.•The superiority of the proposed techniques is shown.•A proposed framework for the forest algorithm for handling class imbalance.

论文关键词：Software defect prediction,Decision forest,Cost-sensitive,Forest voting,Class imbalance

论文评审过程：Received 29 October 2014, Revised 26 February 2015, Accepted 27 February 2015, Available online 10 March 2015.

论文官网地址：https://doi.org/10.1016/j.is.2015.02.006