Investigation of performance metrics in regression analysis and machine learning-based prediction models

Performance metrics (Evaluation metrics or error metrics) are crucial components of regression analysis and machine learning-based prediction models. A performance metric can be defined as a logical and mathematical construct designed to measure how close the predicted outcome is to the actual result. A variety of performance metrics have been described and proposed in the literature. Knowledge about the metrics' properties needs to be systematized to simplify their design and use. In this work, we examine various regression related metrics (14 in total) for continuous variables, including the most widely used ones, such as the (root) mean squared error, the mean absolute error, the Pearson correlation…