The week's pick
Random Articles
Reseach Article
Hyper-Quad-Tree based K-Means Clustering Algorithm for Fault Prediction
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 76 - Number 5 |
| Year of Publication: 2013 |
| Authors: Swati Varade, Madhav Ingle |
10.5120/13241-0688
|
Swati Varade, Madhav Ingle . Hyper-Quad-Tree based K-Means Clustering Algorithm for Fault Prediction. International Journal of Computer Applications. 76, 5 ( August 2013), 6-10. DOI=10.5120/13241-0688
Abstract
Many researchers examined the need for the development of fault-free software and increase the efficiency of presented algorithms. An optimization of existing algorithms and software fault prediction are two important techniques. It is proven that this technique has to be useful in increasing effectiveness of software, software testing, examining progression costs and achieving results. This paper illustrates hyper quad tree based k-means algorithm for software fault prediction. This system overcomes the weaknesses in k-means algorithm using Hyper Quad Tree as compared to Quad Tree. Hyper quad tree works in n-dimensions hence it finds better initial cluster centers than former algorithms. This constraint of k-means algorithm is try to solve by hyper quad tree. Another crisis is that k-means is very susceptible to the noise , which is also removed by hyper quad tree algorithm.
References
- P. S. Bishnu and V. Bhattacherjee, Member, IEEE" Software Fault Prediction Using Quad Tree-Based K-Means Clustering Algorithm" IEEE Transactions on Knowledge and Data Engineering, Vol. 24, No. 6, June 2012
- P. S. Bishnu and V. Bhattacherjee, "Outlier Detection Technique Using Quad Tree," Proc Int'l Conf. Computer Comm. Control and Information Technology, pp. 143-148, Feb. 2009.
- P. S. Bishnu and V. Bhattacherjee, "Application of K-Medoids with kd-Tree for Software Fault Prediction," ACM Software Eng. Notes, vol. 36, pp. 1-6, Mar. 2011.
- V. Bhattacherjee and P. S. Bishnu, "Software Fault Prediction Using KMedoids Algorithm," Proc. Int'l Conf. Productivity, Quality, Reliability, Optimization and Modeling (ICPQROM '11), p. 191, Feb. 2011.
- J. Han and M. Kamber, "Data Mining Concepts and Techniques", second Ed, pp. 401-404. Morgan Kaufmann Publishers, 2007.
- Parvinder S. Sandhu, Jagdeep Singh, Vikas Gupta, Mandeep Kaur, Sonia Manhas, Ramandeep Sidhu" A K-Means Based Clustering Approach for Finding Faulty Modules in Open Source Software Systems" ,World Academy of Science, Engineering and Technology 48 2010
- Michael Laszlo and Sumitra Mukherjee, Member, IEEE, "A Genetic Algorithm Using Hyper-Quad trees for Low-Dimensional K-means Clustering", IEEE transactions on pattern analysis and machine intelligence, vol. 28, no. 4, April 2006
- Leela Rani. P, Rajalakshmi. P," Clustering Gene Expression Data using Quad-tree based Expectation Maximization Approach" International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 2– No. 2, June 2012 – www. ijais. org
- Meenakshi PC, Meenu S, Mithra M, Leela Rani. P," Fault Prediction using Quad-tree and Expectation Maximization Algorithm", International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868 Foundation of Computer Science FCS, New York, USA Volume 2– No. 4, May 2012 – www. ijais. org
- P. S. Bishnu and V. Bhattacherjee "A New Initialization Method for K-Means Algorithm Using Quad Tree", Proc. Nat'l Conf. Methods and Models in Computing (NCM2C), pp. 73-81, 2008.
- http://promisedata. org/, 2012.
- Swati M. Varade, Prof. M. D. Ingle,"Overview of Software Fault Prediction using Clustering Approaches and Tree Data Structure, "The International Journal of Engineering And Science (IJES),Volume 1 ,Issue 2 Pages239-242 2012 ISSN: 2319 – 1813 ISBN: 2319 – 1805.
Index Terms
Keywords