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Design of 2-Level Clustering Framework for Time Series Data Sets

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 131))

Abstract

Clustering an important issue in the analysis of data like science, technology, social science, biology and medicine. This paper presents an approach the Design of 2-Level Clustering Framework (D2LCF) for Time Series Data Sets. The D2LCF approach is an integration of Level-1 Clustering and Level-2 Clustering. The D2LCF includes the different phases like Input collection, Transformation Clustering Process and Results Analysis. The performance evaluation of Experimental Results has done using SAS9.2 analytical Tool. The Experimental Results show that the proposed approach out performs.

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Correspondence to G. S. Thakur .

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Thakur, G.S., Thakur, R.S., Thakur, R.S. (2012). Design of 2-Level Clustering Framework for Time Series Data Sets. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 131. Springer, New Delhi. https://doi.org/10.1007/978-81-322-0491-6_20

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  • DOI: https://doi.org/10.1007/978-81-322-0491-6_20

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-0490-9

  • Online ISBN: 978-81-322-0491-6

  • eBook Packages: EngineeringEngineering (R0)

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