In today's fast pacing, highly competiting,volatile and challenging world, companies highly rely on data analysis obtained from both offline as well as online way to make their future strategy, to sustain in the market. This paper reviews the regression technique analysis on a real time web data to analyse different attributes of interest and to predict possible growth factors for the company, so as to enable the company to make possible strategic decisions for the growth of the company.

1. Sapna Jain, M Afsar Aalam, M N Doja,"K-Means Clustering using Weka Interface", Proceedings of the fourth national conference, INDIACom-2010.
2. Narendra Sharma,Aman Bajpai, Ratnesh Litoriya,"Comparison the various clustering algorithm of Weka Tools",International Journal of Emerging Technology and Advanced Engineering,ISSN 2250-2459, Volume 2,Issue 5,May 2012
3. Mohd Fauzi Bin Othman,Thomas Moh Shan Yau,"Comparison of different classification Techniques using Weka for Breast Cancer",BioMed 06,IFMBE Proceeding 15,pp 520-523,2007
4. Shilpa Dhanjibhai Serasiaya ,Neeraj Chaudhary ,"Simulation of various classification results using Weka",International Journal of Recent Technology and Engineering ,Volume 1 ,Issue 3 2012 PP 155-158
5. Aaditya Desai,Sunil Rai,"Analysis of Machine Learning Algorithm using Weka",In proceedings of International Conference and Workshop on Emerging Trends in Technology,(TCET,2012)
6. Sabri Pllana, Ivan Janciak,Peter Brezany,Alexander Wohrer," A survey of the state of the art in data mining and the integration query language",in proceedings of 2011 international conference on network based information system.
7. J Han and M. Kamber,"Data Mining Concepts and Techniques", Morgan Kauffman Publisher.
8. Website to download text editing tool for WEKA notepad-plus-plus. org
9. URL to download WEKA http://www. cs. waikato. ac. nz/ml/weka/
10. Mark hall,Eibe Frank,Geoffrey Holmes,Bernhard Pfahringer ,Peter Reutmann ,Ian H. Witter," The WEKA data mining software :An Update ",Sikdd Exploration ,Vol. 11,Issue 1 PP. 10-19.
11. S. Saigal, D. Mehrotra ,"Performance comparison of time series data using predictive data mining techniques" ,Advances in Information Mining ,Vol. 4 ,Issue 1 pp 57-66 2012
12. Weiss S. M. and Indurkhya N. (1999) Predictive Data Mining: A Practical Guide, 1st ed. , Morgan Kauffmann Publishers.
13. Lucarella, D. ,:Unceratinty in information retrieval:an approach based on fuzzy setsIin proceedings of 9th annual international phoenix conference on computer and communication,Arizona,USA ,pp. 809-814(1990)
14. M. Hechermann," An Experimental comparison of several clustering and initialization methods". technical Report MSRTR-98-06,Microsoft Research ,Redmond

Datamining Weka Regression