PERFORMANCE EVALUATION OF DATA MINING TECHNIQUES USING CANCER DATASET

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 cancer dataset and analyzed the performance of partition based algorithms. The two types of partition based algorithms namely Kmeans Plus and Affinithy Propagation are implemented. Comparative analysis of clustering algorithms is also carried out using two different dataset Colon and Leukemia. The performance of 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 dataset and algorithm will be most suitable for analysis of cancer data