RBF Neural Network (RBFNN) using Density Based Clustering for Liver Disorder Dataset
Sunila Godara, Rishipal Singh, Sanjeev Kumar · International Journal of Advanced Research in Computer Science and Software Engineering · 2017
Clustering is an unsupervised classification that is the partitioning of a data set in a set of meaningful subsets. Each object in dataset shares some common property- often proximity according to some defined distance measure. In this paper we will extend our previous work [15]. Simple K-means and Proposed makeDensityBased Clustering (MDBC) are embedded in RBF Neural Network (RBFNN). We evaluated the performance of RBFNN using K-Means and Proposed makeDensityBased Clustering on Liver Disorder Dataset. Proposed algorithm is superior to the existing makeDensityBased Clustering algorithm [15], but it is not capable of performing well when it is embedded with RBFNN.