A Framework for the Evaluation of Machine Learning Algorithms based on Fuzzy AHP and VIKOR

Abstract

Decision-makers consider various criteria, sub-criteria, alternatives, scores, and other parameters for choosing a tool. The problem is decision-making considering objectives that conflict with complex factors such as social, economic, political, technological, or environmental. It is not possible to make decisions based on a single criterion. The objective is to develop a framework for evaluating decisions based on fuzzy logic by hybridizing the fuzzy-AHP and VIKOR methods to select ML algorithms that increase these algorithms' effectiveness in specific problems. The methodology used in this proposal is oriented to exploratory research that allows to identify and define a problem or issue with a quantitative approach.