Google Scholar

##plugins.themes.academic_pro.article.sidebar##

Published
Oct 18, 2014
Download
PDF
Statistic
Read Counter : 91 Download : 72

Downloads

Download data is not yet available.

##plugins.themes.academic_pro.article.main##

Abstract

Data mining is the rising research area to overcome various queries and classification. It is one of the major problems in the area of data mining. In this article, we used J48 algorithm of the WEKA interface. It can be utilized for testing various datasets. J48 algorithm is based on C4.5 decision based learning. Weka is a collection of machine learning algorithms for data mining tasks. The algorithm can be applied directly to a data set or called from your own java code. Ebola virus is affected to the human kind from the affected animals. Proper care must be taken while contacting with the blood or bodily fluids of the affected animals. Proper care must be taken in case of clothing and cooking meat. Fruit bats are the main carriers of this virus. This disease has high risk of death. In this paper publication, the symptoms indicating Ebola have been analyzed in order to identify and cure the victims of the Ebola virus.

Keywords: Data Mining, WEKA, J48, Ebola virus, Decision Tree,

##plugins.themes.academic_pro.article.details##

Author Biographies

J Uma Mahesh, BIET

Faculty of CSE, Assistant Professor

K.V. Naganjaneyulu, BIET

Faculty of CSE, Professor

P. Likitha, BIET

Student, Dept of CSE, BIET

K.N.S. Sindhu Aishwarya, BIET

Student, Dept of CSE, BIET
How to Cite
Mahesh, J. U., Naganjaneyulu, K., Likitha, P., & Aishwarya, K. S. (2014). Analysis of J48 Algorithm in Classification-Ebola Virus. International Journal of Emerging Trends in Science and Technology, 1(08). Retrieved from http://igmpublication.org/ijetst.in/index.php/ijetst/article/view/366

References

1. Tina R. Patil, Mrs. S. S. Sherekar Sant Gadgebaba Amravati University, Amravati Performance Analysis of Naive Bayes and J48 Classification Algorithm for Data Classification
2. Xie, W. and Z. Huimin. A talent markets analysis method based on data mining. in Inteligent Computing and Inteligent Systems (ICIS), 2010 IEE International Conference on. 2010.
3. Kumar, V., et al., Asesing the Efect of Marketing Investments in a Busines Marketing Context. Marketing Science,201. 30(5): p. 924-940.
4. Aylmer, R.J, Who Makes Marketing Decisions in the Multinational Firm? Journal of Marketing, 1970. 34(4): p. 25-30.
5. Shaw, M.J, et al., Knowledge management and data mining for marketing. Decision suport systems, 201. 31(1): p.127-137.
6. Surma, J. and A. Furmanek. Improving Marketing Response by Data Mining in Social Network. in Advances in SocialNetworks Analysis and Mining (ASONAM), 2010 International Conference on. 2010.
7. Margaret H. Danham,S. Sridhar, ”Data mining, Introductory and Advanced Topics”, Person education , 1sted., 2006
8. Wenke Lee, Salvatore J. Stolfo, Kui W. Mok, “A Data Mining Framework for Building Intrusion Detection Models”