A Study of Clustering Techniques using Weka

Data mining uses algorithms to extract information, patterns derived by the Knowledge Discovery in Database (KDD) process. Clustering is important part of data mining. In Weka tool there are three GUI i.e. explorer, experimenter and knowledge flow. This paper describes clustering techniques using Weka open source tool. Here for clustering study diabetes dataset is used with 9 attributes and 768 instances. After using clustering technique it is observed that Weka tool gives similar results using K-means and filtered-cluster.

Provided by: International Journal of Computer Science and Management Research (IJCSMR) Topic: Data Management Date Added: Mar 2014 Format: PDF

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