A Hybrid Model of Neural Network and Grey Wolf Optimization to Predict Diabetes
Data mining is a process of identifying hidden patterns, modeling large amount of data to find relationships useful to data analyst. Now-a-days it has become a major popular technique in desperate research field due to its boundless approaches and applications. In this paper there is hybridization of two methods i.e, Grey Wolf Optimization (GWO) and Artificial Neural Network (ANN) for predicting diabetes (using PIMA Indian Dataset). Grey Wolf Optimization is a global search method and it helps artificial neural network to calculate initial optimal weights and biases and also enhances the performance of Back Propagation Neural Network (BPNN) by increasing convergence speed and better accuracy.
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