Minimal ANN (MANN) model for data classification

Data classification is a prime task in data mining. Accurate and simple data classification task can help the clustering of large dataset appropriately. In this paper we have experimented and suggested a simple ANN based classification models called as minimal ANN (MANN) for different classification problems. The GA is used for optimally finding out the number of neurons in the single hidden layered model. Further, the model is trained with back propagation (BP) algorithm and GA (genetic algorithm) and classification accuracies are compared. It is revealed from the simulation that our suggested model can be a very good candidate for many applications as these are simple with good performances.