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Artificial neural network (ANN) has a wide variety of practice for the solution of problems in the area of data classification. Back propagation algorithm is a famous neural network (NN) traditional training approach. Since this classical training technique has many drawbacks like stuck in the local minima, maximum number of iterations required, in this paper the training of the NN has been implemented with the opposition based with particle swarm optimization neural network (OPSONN) algorithm. These algorithms that are used for the NN training can be applied for the solutions of data classification problems. It is renowned that different techniques comparison is also as vital as by proposing a new technique for data classification. In this paper, a detailed comparative performance analysis for the training of neural network is observed on the different data sets taken from UCI repository. Results demonstrates that …