Journal of Engineering and Applied Sciences

Year: 2014
Volume: 9
Issue: 7
Page No. 249 - 253

Metrics Free Techniques and Issues to Acquire Unifeatured High Density Quality Clusters

Authors : G. Abel Thangaraja, Saravanan Venkataraman Tirumalai and A. Pankaj Moses Monickaraj

References

Gupta, S.C. and V.K. Kapoor, 2010. Fundamentals of Mathematical Statistics. 1st Edn., Sultan Chand and Sons, New Delhi.

Halkidi, M., Y. Batistakis and M. Vazirgiannis, 2002. Cluster validity methods: Part I. ACM SIGMOD Record, 13: 40-45.
CrossRef  |  Direct Link  |  

Jeyabalaraja, V. and E.T. Prabakaran, 2012. Study on software process metrics using data mining tool: A rough set theory approach. Int. J. Comput. Applic., 47: 1-5.
CrossRef  |  Direct Link  |  

Marx, Z., I. Dagan, J.M. Buhmann and E. Shamir, 2002. Coupled clustering: A method for detecting structural correspondence. J. Machine Learn. Res., 3: 747-780.
Direct Link  |  

Rai, P. and S. Singh, 2005. A survey of clustering techniques. Int. J. Comput. Appl., 7: 1-5.
CrossRef  |  Direct Link  |  

Shtern, M. and V. Tzerpos, 2012. Clustering methodologies for software engineering. Adv. Software Eng. 10.1155/2012/792024

Sileshi, M. and B. Gamback, 2009. Evaluating clustering algorithms: Cluster quality and feature selection in content-based image clustering. WRI World Congress Comput. Sci. Inform. Eng., 6: 435-441.
CrossRef  |  Direct Link  |  

Strehl, A. and J. Ghosh, 2002. Cluster ensembles: A knowledge reuse framework for combining multiple partitions. J. Mach. Learn. Res., 3: 583-617.
Direct Link  |  

Yang, B., X. Zheng and P. Guo, 2006. Software metrics data clustering for quality prediction. Proceedings of the Part II International Conference on Intelligent Computing, August 16-19, 2006, Kunming, China, pp: 959-964.

Design and power by Medwell Web Development Team. © Medwell Publishing 2024 All Rights Reserved