Imbalanced pattern recognition: Concepts and evaluations

In this paper we propose and investigate a concept of imbalanced pattern recognition problems and evaluation methods of solutions applied to solve such problems. The attention is focused on so called paper-to-computer technologies, but it is not limited to them due to possible direct generalization to other domains. Besides bringing a concept of imbalanced pattern recognition problem, classification quality from the perspective of single classes is considered. Parameters of binary classification and parameters and measures used in signal detection theory are adopted. Quality of classification in terms of one class contra all others is taken into account. Then, classifiers performance in frames of one class at the background of other classes and in frames of impact of other classes on the given on are evaluated. Finally, parameters characterizing global properties of classification are introduced and illustrated.