An incremental type-2 fuzzy classifier for stock trend prediction

作者：

Highlights：

• An interval type-2 fuzzy model for online prediction of stock market’s future trend.

• Capable of considering a high amount of uncertainty in stock data.

• Membership degrees are extracted from information of data not human knowledge.

• The proposed algorithm incrementally extracts type-2 fuzzy sets.

• The method has low computational complexity.

摘要

•An interval type-2 fuzzy model for online prediction of stock market’s future trend.•Capable of considering a high amount of uncertainty in stock data.•Membership degrees are extracted from information of data not human knowledge.•The proposed algorithm incrementally extracts type-2 fuzzy sets.•The method has low computational complexity.

论文关键词：Stock trend prediction,Machine learning,Interval type-2 fuzzy classifier,Incremental learning,Uncertainty handling,Stock market,Concept drift

论文评审过程：Received 21 February 2022, Revised 21 July 2022, Accepted 4 September 2022, Available online 13 September 2022, Version of Record 19 September 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118787