Abstract-The selection of the best classification algorithm for a given dataset is a very widespread problem. It is also a complex one, in the sense it requires to make several important methodological choices. Among them, in this work we focus on the measure used to assess the classification performance and rank the algorithms. We present the most popular measures and discuss their properties. Despite the numerous measures proposed over the years, many of them turn out to be equivalent in this specific case. They can also lead to interpretation problems and be unsuitable for our purpose. Consequently, the classic overall success rate or marginal rates should be preferred for this specific task.
A paper REF by Vincent Labatut and Hocine Cherifi has focussed on the measure used to assess the classification performance and rank the algorithms.
Accuracy Measures for the Comparison of Classifiers
ArXiv
ArXiv
Computer Science Mathematics