Comparison of Two Clustering Techniques Case Study: Breast Cancer Data

Abstract

The main goal of this thesis is to study two clustering methods practically. The aims of practical study are to find out the capabilities of these two methods in clustering the breast cancer data set. Many clusters have been generated using both k-means and Two-step. Extensive comparisons have been conducted. The main conclusion is that these two methods generate different clusters. The main reason could be the difference in their strategies. Further, studies are needed to find more reasons.