Visualizing and classifying data using a hybrid intelligent system

In this paper, a hybrid intelligent system that integrates the SOM (Self-Organizing Map) neural network, kMER (kernel-based Maximum Entropy learning Rule), and Probabilistic Neural Network (PNN) for data visualization and classification is proposed. The rationales of this Probabilistic SOM-kMER model are explained, and its applicability is demonstrated using two benchmark data sets. The results are analyzed and compared with those from a number of existing methods. Implication of the proposed hybrid system as a useful and usable data visualization and classification tool is discussed.<br />