Feature subset selection Filter–Wrapper based on low quality data

作者:

Highlights:

• Low quality data (LQD) appear in real problems. We incorporate the processing of LQD in feature selection.

• We propose a feature selection method that works within the framework of the fuzzy logic theory.

• Our approach is classified as a hybrid method that combines the filter and wrapper methods.

• The experiments evaluate the performance of the approach with low quality and microarray datasets.

• The results indicate that the approach has a good classification performance with or without LQDs.

摘要

•Low quality data (LQD) appear in real problems. We incorporate the processing of LQD in feature selection.•We propose a feature selection method that works within the framework of the fuzzy logic theory.•Our approach is classified as a hybrid method that combines the filter and wrapper methods.•The experiments evaluate the performance of the approach with low quality and microarray datasets.•The results indicate that the approach has a good classification performance with or without LQDs.

论文关键词:Feature selection,Low quality data,Fuzzy Random Forest,Fuzzy Decision Tree

论文评审过程:Available online 31 May 2013.

论文官网地址:https://doi.org/10.1016/j.eswa.2013.05.051