Locality adaptive preserving projections for linear dimensionality reduction

作者：

Highlights：

• Seeking the local structure in original feature space is shown to be error-prone.

• We propose a locality adaptive projection approach for neighborhood preserving.

• Experimental results demonstrate the feasibility of the proposed method.

摘要

•Seeking the local structure in original feature space is shown to be error-prone.•We propose a locality adaptive projection approach for neighborhood preserving.•Experimental results demonstrate the feasibility of the proposed method.

论文关键词：Dimensionality reduction,Feature extraction,Intrinsic dimensionality,Local structure

论文评审过程：Received 23 June 2019, Revised 8 February 2020, Accepted 2 March 2020, Available online 4 March 2020, Version of Record 9 March 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113352