Clustering Algorithms: Study and Performance Evaluation Using Weka Tool
Pages : 1094-1098
Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Clustering is a procedure to organizing the objects in to groups or clustered together, based on the principle of maximizing the intra-class similarity and minimizing the inter class similarity. The various clustering algorithms are analyzed and compare the performance of clustering algorithms on aspect for time taken to build the model, Epsilon, minpts. The aim is to judge the efficiency of different data mining algorithms on diabetic dataset and determine the optimum algorithm. The performance analysis depends on many factors encompassing test mode, distance function and parameters.
Key words: Data mining, cluster analysis, clustering algorithms, distance function, Weka 3.6.9 tools, Performance analysis
Article published in International Journal of Current Engineering and Technology, Vol.3,No.3(Aug- 2013)