Analysis on Misclassification in Existing Contraction of Fuzzy Min–max Models

• Main Authors: Alhroob, Essam, Mohammed, Mohammed Falah, Al Sayaydeh, Osama Nayel, Hujainah, Fadhl, Ngahzaifa, Ab. Ghani
• Format: Conference or Workshop Item
• Language: English
• Published: Springer International Publishing 2020
• Subjects: QA Mathematics
• Online Access: http://umpir.ump.edu.my/id/eprint/25535/1/Analysis%20on%20Misclassification%20in%20Existing.pdf; http://umpir.ump.edu.my/id/eprint/25535/; https://doi.org/10.1007/978-3-030-33582-3_26
• Institution: Universiti Malaysia Pahang

Fuzzy min–max (FMM) neural network is one of the most powerful models for pattern classification. Various models have been introduced based on FMM model to improve the classification performance. However, the misclassification of the contraction process is a crucial issue that has to be handled in F...