Scent classification by K nearest neighbors using ion-mobility spectrometry measurements

作者：

Highlights：

• K Nearest Neighbor classifies scents and their chemical components.

• Scents/ chemicals are classified using only ion-mobility spectrometry measurements.

• Classification using k-dimensional tree search is approximately 8-times faster.

• By principal component analysis 71–86% of features are ignored for classification.

摘要

•K Nearest Neighbor classifies scents and their chemical components.•Scents/ chemicals are classified using only ion-mobility spectrometry measurements.•Classification using k-dimensional tree search is approximately 8-times faster.•By principal component analysis 71–86% of features are ignored for classification.

论文关键词：Machine learning,K nearest neighbours,Ion-mobility spectrometry,Scent classification

论文评审过程：Received 17 September 2017, Revised 23 August 2018, Accepted 24 August 2018, Available online 28 August 2018, Version of Record 7 September 2018.

论文官网地址：https://doi.org/10.1016/j.eswa.2018.08.042