Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6857643 | Information Sciences | 2015 | 18 Pages |
Abstract
Performance measures are used in various stages of the process aimed at solving a classification problem. Unfortunately, most of these measures are in fact biased, meaning that they strictly depend on the class ratio - i.e. on the imbalance between negative and positive samples. After pointing to the source of bias for the best known measures, novel unbiased measures are defined which are able to capture the concepts of discriminant and characteristic capability. The combined use of these measures can give important information to researchers involved in machine learning or pattern recognition tasks, in particular for classifier performance assessment and feature selection.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Giuliano Armano,