Performance Metrics (Error Measures) in Machine Learning Regression, Forecasting and Prognostics: Properties and Typology

Understand

Performance metrics (error measures) are vital components of the evaluation frameworks in various fields.

• The intention of this study was to overview of a variety of performance metrics and approaches to their classification.
• The main goal of the study was to develop a typology that will help to improve our knowledge and understanding of metrics and facilitate their selection in machine learning regression, forecasting and prognostics.
• Based on the analysis of the structure of numerous performance metrics, we propose a framework of metrics which includes four (4) categories: primary metrics, extended metrics, composite metrics, and hybrid sets of metrics.