Not always simple classification: Learning SuperParent for class probability estimation

作者：

Highlights：

• Accurate class probability estimation is also desirable in many applications.

• We investigated the class probability estimation performance of SuperParent.

• We proposed an improved SuperParent algorithm based on conditional log likelihood.

• Experimental results on a large number of datasets validate its effectiveness.

摘要

•Accurate class probability estimation is also desirable in many applications.•We investigated the class probability estimation performance of SuperParent.•We proposed an improved SuperParent algorithm based on conditional log likelihood.•Experimental results on a large number of datasets validate its effectiveness.

论文关键词：SuperParent,CLL-SuperParent,Conditional log likelihood,Classification accuracy,AUC

论文评审过程：Available online 5 March 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.02.049