基于模糊层次分析法和VIKOR的机器学习算法评价框架

Maikel Leyva-Vázquez, Francisco-Javier Poma-Torres, Galo-Enrique Valverde-Landivar Miguel-Angel Quiroz-Martinez
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引用次数: 0

摘要

决策者在选择工具时考虑各种标准、子标准、备选方案、分数和其他参数。问题在于决策时要考虑到与社会、经济、政治、技术或环境等复杂因素相冲突的目标。不可能根据单一标准作出决定。目标是通过混合模糊ahp和VIKOR方法来选择ML算法,以提高这些算法在特定问题中的有效性,从而开发一个基于模糊逻辑的评估决策的框架。本提案中使用的方法以探索性研究为导向,允许用定量方法识别和定义问题或问题。
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A Framework for the Evaluation of Machine Learning Algorithms based on Fuzzy AHP and VIKOR
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.
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