Abstract—Fuzzy clustering is an important approach in data mining. It has been applied broadly in many aspects and receiving great attention from enterprisers and scholars. This paper makes use of MATLAB language to produce a fuzzy clustering algorithm for classifying the batting statistics of Indian Premier League (IPL) T-20 version-3 cricket tournament into several numbers of clusters. The definition of clusters as well as the membership function has been implemented using MATLAB. The results obtained from Indian premier league batting statistics dataset detect n-clusters to handle the imprecise and ambiguous result. Finally, this article proposed a fuzzy clustering technique which provides efficient and accurate data analysis in the field of data mining.
Index Terms—Cluster analysis, fuzzy set theory, machine learning, data mining.
Pabitra Kumar Dey is with Department of Computer Application, Dr.B.C.Roy Engineering College, Durgapur, India (Emaildey_ firstname.lastname@example.org)
Gangotri Chakraborty is with Manipal University, India. Purnendu Ruj is with Department of Computer Science and Engineering, Dr.B.C.Roy Engineering College, Durgapur, India.
Suvobrata Sarkar is with Department of Computer Science and Engineering, Dr.B.C.Roy Engineering College, Durgapur, India.
Cite: Pabitra Kumar Dey, Gangotri Chakraborty, Purnendu Ruj, and Suvobrata Sarkar, "A Data Mining Approach on Cluster Analysis of IPL," International Journal of Machine Learning and Computing vol. 2, no. 4, pp. 351-354, 2012.