ARCHIVES

1. Han, J., Kamber, M.: “Data Mining Concepts and Techniques”, Morgan Kaufmann Publishers, 2006.
2. “Data mining: Introductory and Advanced Topics” Margaret H. Dunham
3. JyotiSoni, Ujma Ansari, Dipesh Sharma, SunitaSoni “Predictive Data Mining for Medical Diagnosis: An Overview of Heart Disease
Prediction” IJCSE Vol. 3 No. 6 June 2011.
4. Carloz Ordonez, “Association Rule Discovery with Train and Test approach for heart disease prediction”, IEEE Transactions on
Information Technology in Biomedicine, Volume 10, No. 2, April 2006.pp 334-343.
5. M. ANBARASI, E. ANUPRIYA, N.CH.S.N.IYENGAR, “Enhanced Prediction of Heart Disease with Feature Subset Selection using
Genetic Algorithm”, International Journal of Engineering Science and Technology Vol. 2(10), 2010, 5370- 5376.
6. G. Parthiban, A. Rajesh, S.K.Srivatsa “Diagnosis of Heart Disease for Diabetic Patients using Naive Bayes Method” .
7. BellaachiaAbdelghani and ErhanGuven, "Predicting Breast Cancer Survivability using Data Mining Techniques,"Ninth Workshop on
Mining Scientific and Engineering Datasets in conjunction with the Sixth SIAM International Conference on Data Mining,” 2006.
8. R. GeethaRamani, G. Sivagami, Parkinson Disease Classification using Data Mining Algorithms, International Journal of Computer
Applications (0975 – 8887) Volume 32– No.9, October 2011.
9. ShomonaGracia Jacob, R.GeethaRamani, Discovery of Knowledge Patterns in Clinical Data through Data Mining Algorithms:
Multiclass Categorization of Breast Tissue Data, International Journal of Computer Applications (0975 – 8887) Volume 32– No.7,
October 2011.
10. S. Poonkuzhali, R. GeethaRamani, R. Kishore Kumar,Efficient Classifier for TP53 Mutants using Feature Relevance Analysis, in
International Multiconference of Engineers and computer scienctists, Vol 1, 2012.
11. Tanagra-Data Mining tutorials http://data-mining- tutorials.blogspot.com
12. Arun K Pujari, Data Mining Techniques, University Press 2001
13. ShwetaKharya, "International Journal of Computer Science, Engineering and Information Technology (IJCSEIT)", Vol.2, No.2, April
2012.
14. Christina Schweikert, Yanjun Li, David Dayya, David Yens, Martin Torrents, D. Frank Hsu,” Analysis of Autism Prevalence and
Neurotoxins Using Combinatorial Fusion and Association Rule Mining”, in Ninth IEEE International Conference on Bioinformatics
and Bioengineering, 2009.
15. M.S. Mythili, A.R.MohamedShanavas,” A Novel Approach to Predict the Learning Skills of Autistic Children using SVM and Decision
Tree”, in (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 5 (6) , 2014.
16. M.S.Mythili, A. R. Mohamed Shanavas,” A Study on Autism Spectrum Disorders using Classification Techniques”, in International
Journal of Soft Computing and Engineering (IJSCE) ISSN:2231- 2307,Volume-4Issue-5,November2014.