On measuring the complexity of classification problems

Abstract

There has been a growing interest in describing the difficulty of solving a classification problem. This knowledge can be used, among other things, to support more grounded decisions concerning data preprocessing, as well as for the development of new data-driven pattern recognition techniques. Indeed, to estimate the intrinsic complexity of a classification problem, there are a variety of measures that can be extracted from a training data set. This paper presents some of them, performing a theoretical analysis.