THE SYSTEM OF CRITERIA FOR FEATURE INFORMATIVENESS ESTIMATION IN PATTERN RECOGNITION - Oliinyk, A.; Subbotin, S.; Lovkin, V.; Blagodariov, O.; Zaiko, T. (Radio Electronics, Computer Science, Control, 2018)
Context. The task of automation of feature informativeness estimation process in diagnostics and pattern recognition problems i solved. The object of the research is the process of informative feature selection. The subject of the research are the criteria of feature informativeness estimation. Objective. The research objective is to develop the system of criteria for feature informativeness estimation which enables to comput informativeness of interdependent feature sets. Method. The system of criteria for feature informativeness estimation is proposed. The proposed system is based on the idea tha feature significance is computed according to spatial location of observations of different classes (size of changing of output parameter) The developed criteria system enables to estimate individual and group feature informativeness in classification and regression problems in situations when initial data samples contain redundant and interdependent features as well as observations with missing values. The proposed criteria don’t require to construct models based on the estimated feature combinations, in such a way considerably reducing time and computing costs for informative feature selection. Application of the proposed criteria for estimation and selection of informative feature allows to reduce structural complexity of synthesized diagnosis and recognition models, to raise its interpretability and generalization ability due to removing of insignificant, interdependent and redundant features in diagnostics and pattern recognition problems. Results. The software which implements the proposed system of criteria for feature informativeness estimation and allows to selec informative features for synthesis of recognition models based on the given data samples has been developed. Conclusions. The conducted experiments have confirmed operability of the proposed system of criteria for feature informativenes estimation and allow to recommend it for processing of data sets for pattern recognition in practice. The prospects for further researche may include the modification of the known feature selection methods and the development of new ones based on the proposed system o criteria for individual and group feature informativeness estimation.