Abstract

The article gives an overview of the Radial Basis Function which is combined\nwith Fuzzy C-Means algorithms and its learning process made by Projection Based\nLearning which is pointed out as PBL-FRBF The Projection Based Learning decreases the\nlearning time, finds optimum output weight by its energy function and it prefers small\namount of samples for testing. The performance of a classification content not only depends\non learning algorithm selected but it also depends on the selection of dataset. Performance\nanalysis is evaluated by benchmark datasets for classification problem from the UCI\nmachine learning repository of the four datasets two of them are termed to be as balanced\nand the remaining as imbalanced dataset. The performance of the proposed PBL-FRBF has\nproduced superior results compared with Fuzzy Radial Basis Function and Radial Basis\nFunction for classification problems.