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Coalescing Clustering and Classification

Publication Type : Conference Paper

Publisher : (SEISCON 2012), IET

Source : IET Chennai 3rd International on Sustainable Energy and Intelligent Systems (SEISCON 2012), IET, Tiruchengode, India (2012)

Url : https://ieeexplore.ieee.org/document/6719160

Campus : Chennai

School : Department of Computer Science and Engineering, School of Engineering

Department : Computer Science

Year : 2012

Abstract : In Data Mining Clustering and Classification are two important techniques. In this paper we make use of large database (Diabetes dataset containing) to perform an integration of clustering and classification technique. We compared the results of simple classification technique (J48 classifier) with the results of integration of clustering (X-Means) and classification (J48) techniques based upon various parameters using WEKA (Waikato Environment for Knowledge Analysis) a data mining tool. The results of the experiment show that integration of clustering and classification gives promising results with utmost accuracy rate even when the dataset contains missing values.

Cite this Research Publication : G. B. Mohan, R. Prasanna Kumar, and Ravi, T., “Coalescing Clustering and Classification”, in IET Chennai 3rd International on Sustainable Energy and Intelligent Systems (SEISCON 2012), Tiruchengode, India, 2012.

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