Thisara - ga optimized nearest neighbor classification framework

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Date

2010-09

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Computer Science & Engineering Society c/o Department of Computer Science and Engineering, University of Moratuwa.

Abstract

Information plays such an important role in almost every human life. We have plenty of data available and for the most effective and efficient use, we need to extract information from them. Data classification to the top in that scenario, where it will indicate its value in terms of business assets. For the problems exist in classification field, such as data mining and other third party applications which involve classifications/predictions in their domains, use their own procedures of classifying the data available, hence slowing down the efficiency due to increase of development time which ultimately results in high development cost. Thisara addresses the above issue by providing a common platform for the classification problems to be implemented upon, without worrying about the underlying complexity of the application, hence reduce bulkiness and provides a stable framework which offers a high performance in real time operation of classifications.

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Keywords

Clustering, Classification, Normalization, GA Optimization

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