A Novel Performance Measure for Machine Learning Classification
Mingxing Gong
Abstract
Machine learning models have been widely used in numerous classification problems and performance measures play a critical role in machine learning model development, selection, and evaluation. This paper covers a comprehensive overview of performance measures in machine learning classification. Besides, we proposed a framework to construct a novel evaluation metric that is based on the voting results of three performance measures, each of which has strengths and limitations. The new metric can be proved better than accuracy in terms of consistency and discriminancy.
Topics & Concepts
Computer scienceMachine learningMetric (unit)Artificial intelligenceConsistency (knowledge bases)Construct (python library)Measure (data warehouse)VotingSelection (genetic algorithm)Data miningEngineeringOperations managementLawPoliticsPolitical scienceProgramming languageMachine Learning and Data ClassificationImbalanced Data Classification TechniquesData Stream Mining Techniques