A new Unsupervised Spectral Feature Selection Method for mixed data: A filter approach

作者：

Highlights：

• A new unsupervised filter feature selection method for mixed data is proposed.

• Spectral feature selection is used for finding relevant features in mixed datasets.

• The most relevant features are placed at the beginning of the ranking.

• Our method overcomes state-of-the-art unsupervised filter feature selection methods.

摘要

•A new unsupervised filter feature selection method for mixed data is proposed.•Spectral feature selection is used for finding relevant features in mixed datasets.•The most relevant features are placed at the beginning of the ranking.•Our method overcomes state-of-the-art unsupervised filter feature selection methods.

论文关键词：Unsupervised feature selection,Spectral feature selection,Mixed data,Feature ranking

论文评审过程：Received 21 January 2017, Revised 26 May 2017, Accepted 19 July 2017, Available online 27 July 2017, Version of Record 17 August 2017.

论文官网地址：https://doi.org/10.1016/j.patcog.2017.07.020