Akihiro Nishihara

Michigan-Style Fuzzy Genetics-Based Machine Learning for Class Imbalance Data

2021 · Journal of Japan Society for Fuzzy Theory and Intelligent Informatics

Recently, interpretability of classifiers has been actively discussed in some real-world applications like medical and financial fields. Michigan-type Fuzzy Genetics-based Machine Learning (FGBML) is one of the most-well known methods for generating fuzzy classifiers with …