Handling the Problem of Unbalanced Data Sets in the Classification of Technical Equipment States - Obukhov Egor (Proceedings of the International Conference on Applied Innovations in IT, 2016)
Questions of handling unbalanced data considered in this article. As models for classification, PNN and MLP are used. Problem of estimation of model performance in case of unbalanced training set is solved. Several methods (clustering approach and boosting approach) considered as useful to deal with the problem of input data.