OPTIMIZATION OF ARTIFICIAL NEURAL NETWORK (ANN) CLASSIFICATION MODEL AND TRAINING DATA FOR APPROPRIATE MODEL BEHAVIOR

This disclosure relates to method and system for optimizing artificial neural network (ANN) classification model and training data thereof for appropriate model behavior. The method may include extracting entities and domain specific entities from the training data for each of classes of the ANN classification mode, determining model parameters of the ANN classification model based on the training data, determining missing data with respect to the training data or the model parameters based on the entities and the domain specific entities for each the classes, iteratively analysing a relative advantage of a modified ANN classification model with a modified training data with respect to the ANN classification model with the training data, and determining an optimized ANN classification model and an optimized training data for appropriate model behavior based on the iterative analysis. The modified data may be generated based on the missing data.