WABL method as a universal defuzzifier in the fuzzy gradient boosting regression model

作者：

Highlights：

• A different representation of triangular fuzzy numbers (TFN) is handled.

• Efficient operations on TFN for regression models are proposed.

• A fuzzy gradient boosting regression algorithm is proposed.

• Experiments on benchmark datasets with various defuzzification methods are made.

• Effectiveness of the WABL defuzzification method as a universal one is shown.

摘要

•A different representation of triangular fuzzy numbers (TFN) is handled.•Efficient operations on TFN for regression models are proposed.•A fuzzy gradient boosting regression algorithm is proposed.•Experiments on benchmark datasets with various defuzzification methods are made.•Effectiveness of the WABL defuzzification method as a universal one is shown.

论文关键词：Fuzzy number,Defuzzificaton,WABL,Gradient boosting regression

论文评审过程：Received 30 May 2022, Revised 31 August 2022, Accepted 2 September 2022, Available online 6 September 2022, Version of Record 9 September 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118771