Fuzzy Integrated Machine Learning: Navigating Uncertainty in Data

Abstract: 

Fuzzy integrated machine learning combines fuzzy theory with machine learning models to enhance performance in data analysis. Fuzzy theory addresses uncertainty in data, making this combination particularly useful for complex problems or situations where data is incomplete or imprecise.

Profile:

Asst. Prof. Mahinda graduated from University of Ruhuna holding B.Sc. Hons degree in Mathematics 2015. He completed his Master’s degree in Computational Engineering at LUT University in 2018 and his Doctor of Science degree in Economics and Business Administration (Major: Business Analytics) in 2022. Thereafter, he began working as a postdoctoral researcher. Currently, Mahinda is an Assistant Professor (Tenure) at Business School (Business Analytics team), LUT University. His research interests include data mining, applied machine learning, fuzzy systems, fuzzy qualitative comparative analysis, and applications in Business and Management (and also other areas).