The incremental Fourier classifier: Leveraging the discrete Fourier transform for classifying high speed data streams

作者：

Highlights：

• Novel incrementally adapting Fourier classifier is proposed.

• Strategy for efficiently computing a synopsis of data is presented.

• Novel instance schema pruning method is illustrated.

• Proposed approach outperforms existing benchmark stream classifying algorithms.

摘要

•Novel incrementally adapting Fourier classifier is proposed.•Strategy for efficiently computing a synopsis of data is presented.•Novel instance schema pruning method is illustrated.•Proposed approach outperforms existing benchmark stream classifying algorithms.

论文关键词：Data stream,Ensemble classifier,Discrete Fourier Transform,Concept drift,Fourier spectrum,Feature selection

论文评审过程：Received 12 August 2017, Revised 11 December 2017, Accepted 12 December 2017, Available online 12 December 2017, Version of Record 15 December 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.12.023