An empirical evaluation of stacked ensembles with different meta-learners in imbalanced classification

• Main Authors: Zian, Seng, Abdul Kareem, Sameem, Varathan, Kasturi Dewi
• Format: Article
• Published: Institute of Electrical and Electronics Engineers 2021
• Subjects: QA75 Electronic computers. Computer science; TA Engineering (General). Civil engineering (General); TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.um.edu.my/27115/
• Institution: Universiti Malaya

The selection of a meta-learner determines the success of a stacked ensemble as the meta-learner is responsible for the final predictions of the stacked ensemble. Unfortunately, in imbalanced classification, selecting an appropriate and well-performing meta-learner of stacked ensemble is not straigh...