Efficient and Robust Ensemble Method for High Dimensional Data Classification Using Radial Basis Functions Neural Network

As we are living in data age, the mountain of data growing exponentially. But the main issue is to identify useful information from it. Data mining provides two ways to recognize valuable information i.e., supervised and unsupervised learning methods. In supervised methods, ensemble methods performing exceptionally good. This paper proposes here the ensemble method to classify high-dimensional data. This method will generate the independent feature subsets. Each independent feature subset is trained using base classifier. These results are combined by majority voting. The proposed method uses the radial basis function neural network to classify data of biomedicine.