Yusuke Nojima

A Novel Classification Method From the Perspective of Fuzzy Social Networks Based on Physical and Implicit Style Features of Data

2019 · IEEE Transactions on Fuzzy Systems

Many practical scenarios have demanded that we should classify unlabeled data more accurately based on both physical features (e.g., color, distance, or similarity) and implicit style features of data. As most extant classification algorithms classify …

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 …