A review on inter-cluster and intra-cluster similarity using bisected fuzzy C-mean technique via outward statistical testing

摘要

Clustering is one of the most important fields of data mining which has a large number of applications in practice. Automatic clustering is done when the input data size cannot be link with the number of clusters are unknown. In the existing research the researchers have performed via Outward Statistical Testing on Density metrics. This performs automatic clustering on data but does not have good Inter-cluster and Intra-cluster similarity metrics. This drawback can remove if we introduce Bisected clustering algorithm like bisecting k-means or bisecting FCM. Our research is to check the performance analysis of existing technique and improve it using Bisected clustering algorithm.