ISSN : 2319-7323


Open Access


Title : Performance Enhancement of Classifiers using Integration of Clustering and Classification Techniques
Authors : G.Keerthana, Dr. V.Srividhya
Keywords : Data mining, classification, integrated clustering-classification, WEKA, Pima Indians Diabetes dataset.
Issue Date : May 2014
Abstract : Medical professionals need a reliable prediction methodology to diagnose Diabetes. Data mining is the process of analysing data from different perspectives and summarizing it into useful information. The main goal of data mining is to discover new patterns for the users and to interpret the data patterns to provide meaningful and useful information for the users. Data mining is applied to find useful patterns to help in the important tasks of medical diagnosis and treatment. In this paper, performance comparison of simple classification algorithms and integrated clustering and classification algorithms are carried out. It was found that the integrated clustering-classification technique was better than the simple classification technique. Data mining tool used is WEKA. PIMA INDIANS DIABETES dataset is used.
Page(s) : 200-203
ISSN : 2319-7323
Source : Vol. 3, No.3