Genetic Optimization of Pattern Classification Using Heart Disease Data

Classification is one of the data mining techniques which is generally used in the prediction of data. Particularly in pattern classification a function is built to map input space into output space using multiple classes. For this purpose, artificial neural networks are very effective to build a model and to test and train the data. For the training process many training algorithms are used to increase the performance. In this paper, we shall make a training of feed forward neural network using Backpropagation algorithm, which is optimized with Genetic Algorithm with heart disease dataset with multiple class. Graphs are plotted to show the accuracy of the classification.