A REVIEW ON DIFFERENT CLUSTERING ALGORITHM FOR CANCER DATA ANALYSIS

Abstract

In recent years DM has attracted great attention in the healthcare industry and society as a whole. The objective of this research work is focused on the cluster creation of two cacancer dataset and analyzed the performance of partition based algorithms. The three tytypes of partition based algorithms namely Global kMeans, Kmeans Plus and Affinithy Prpropagation are implemented. Comparative analysis of clustering algorithms is also cacarried out using two different dataset Colon and Leukemia. The performance of a algorithms depends on the Correctly classified clusters and the Average accuracy of data. The Affinity Propagation algorithm is efficient for clustering the cancer dataset. The final outcome of this work is suitable to analyses the behavior of cancer in the department of oncology in cancer centers. Ultimate goal of this research work is to find out which type of dadataset and algorithm will be most suitable for analysis of cancer data.