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J48 and JRIP Rules for E-Governance Data
Anil Rajput, Ramesh Prasad Aharwal, Meghna Dubey, S.P. Saxena, Manmohan Raghuvanshi
Pages - 201 - 207     |    Revised - 01-05-2011     |    Published - 31-05-2011
Published in International Journal of Computer Science and Security (IJCSS)
Volume - 5   Issue - 2    |    Publication Date - May / June 2011  Table of Contents
MORE INFORMATION
References   |   Cited By (9)   |   Abstracting & Indexing
KEYWORDS
Data Mining, Jrip, J48, WEKA, Classification
ABSTRACT
Data are any facts, numbers, or text that can be processed by a computer. Data Mining is an analytic process which designed to explore data usually large amounts of data. Data Mining is often considered to be \"a blend of statistics. In this paper we have used two data mining techniques for discovering classification rules and generating a decision tree. These techniques are J48 and JRIP. Data mining tools WEKA is used in this paper.
CITED BY (9)  
1 Shanmuganathan, S. (2016). A Hybrid Artificial Neural Network (ANN) Approach to Spatial and Non-spatial Attribute Data Mining: A Case Study Experience. In Artificial Neural Network Modelling (pp. 443-472). Springer International Publishing.
2 Koneru, A. (2014). Knowledge Extraction from Work Instructions through Text Processing and Analysis.
3 Montero, C. (2014). Cost aware real time big data processing in Cloud Environments (Doctoral dissertation, The University of Melbourne).
4 Abebe, H. (2014). Predicting Infant Immunization Status in Ethiopian (Doctoral dissertation, AAU).
5 Parsania, V. S., Jani, N. N., & Bhalodiya, N. H. Applying Naïve bayes, BayesNet, PART, JRip and OneR Algorithms on Hypothyroid Database for Comparative Analysis.
6 Yinkfu Chuye, K. (2013). Design and Implementation of Machine Learning and Rule-Based System for Verifying Automation System Designs.
7 Mandal, S., Saha, G., & Pal, R. K. (2013). An Approach towards Automated Disease Diagnosis & Drug Design Using Hybrid Rough-Decision Tree from Microarray Dataset. J Comput Sci Syst Biol, 6, 337-343.
8 Namayanja, J. M., & Janeja, V. P. (2013, June). Discovery of persistent threat structures through temporal and geo-spatial characterization in evolving networks. In Intelligence and Security Informatics (ISI), 2013 IEEE International Conference on (pp. 191-196). IEEE.
9 Ibrahim, N. H., Mustapha, A., Rosli, R., & Helmee, N. H. (2013). A hybrid model of hierarchical clustering and decision tree for rule-based classification of diabetic patients. International Journal of Engineering and Technology (IJET), 5(5), 3986-91.
ABSTRACTING & INDEXING
1 Google Scholar 
2 CiteSeerX 
3 refSeek 
4 Scribd 
5 SlideShare 
6 PdfSR 
REFERENCES
D. Delen, G. Walker, and A. Kadam, "Predicting breast cancer survivability: A comparison of three data mining methods," Artificial Intelligent in Medicine, 34:113- 127, 2005.
G. K. F. Tso and K. K. W. Yau, "Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks," Energy, 32 : 1761-1768, 2007.
H. Jantan et al. “Classification for Prediction”, International Journal on Computer Science and Engineering, 2(8): 2526-2534, 2010.
J. Han and M. Kamber, “Data Mining: Concept and Techniques”. Morgan Kaufmann (2006).
L. Y. Chang and W. C. Chen, "Data mining of tree-based models to analyze freeway accident frequency," Journal of Safety Research,36(1): 365-375, 2005.
N. Ulutagdemir and Ö. Dagl?, “Evaluation of risk of death in hepatitis by rule induction algorithms”, Scientific Research and Essays, 5(20): 3059-3062, 2010, ISSN 1992-2248.
Weka website: Data Mining Software in Java, http://www.cs.waikato.ac.nz/ml/weka/
MANUSCRIPT AUTHORS
Dr. Anil Rajput
Sadhu Vaswani College, Barkatullah University, Bhopal - India
drar1234@yahoo.com
Mr. Ramesh Prasad Aharwal
- India
Mr. Meghna Dubey
- India
Mr. S.P. Saxena
- India
Mr. Manmohan Raghuvanshi
- India


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