OPTIMIZED POLYNOMIAL FUZZY SWARM NET FOR CLASSIFICATION

This chapter presents a hybrid approach for solving classification problems. We have used three important neuro and evolutionary computing techniques such as Polynomial Neural Network, Fuzzy system, and Particle Swarm Optimization to design a classifier. The objective of designing such a classifier model is to overcome some of the drawbacks in the existing systems and to obtain a model that consumes less time in developing the classifier model, to give better classification accuracy, to select the optimal set of features required for designing the classifier and to discard less important and redundant features from consideration. Over and above the model remains comprehensive and easy to understand by the users.