FT4cip: A new functional tree for classification in class imbalance problems
作者：
Highlights：
• We introduce the Functional Tree for class imbalance problems (FT4cip).
• We make a statistical comparison of FT4cip against rival methods in 110 databases.
• The comparison shows FT4cip has better classification performance than rivals.
• A meta-analysis lets us recommend what classifier to use given a specific problem.
• The meta-analysis shows FT4cip has great performance in class imbalance problems.
摘要
•We introduce the Functional Tree for class imbalance problems (FT4cip).•We make a statistical comparison of FT4cip against rival methods in 110 databases.•The comparison shows FT4cip has better classification performance than rivals.•A meta-analysis lets us recommend what classifier to use given a specific problem.•The meta-analysis shows FT4cip has great performance in class imbalance problems.
论文关键词：00-01,99-00,Decision trees,Functional trees,Model trees,Supervised classification
论文评审过程：Received 28 November 2021, Revised 14 June 2022, Accepted 16 June 2022, Available online 21 June 2022, Version of Record 11 July 2022.
论文官网地址：https://doi.org/10.1016/j.knosys.2022.109294
