• D.Nanthini
• P.Thangaraju

Abstract—Diabetes has become a modern day life style disease affecting millions of people around the world. Data mining is growing in relevance to solving real world problems and hence this can be applied to the diabetes problem as well. The study proposes to use the UCI repository dataset called PIMA Indians Diabetes dataset and decision tree algorithms like C4.5, J48 and FB Tree. The comparison study includes parameters like efficiency, accuracy and features or nodes selected. This hybrid model enables to accurately classify the diabetes dataset and help the people providing treatment as well as those suffering from the disease.

Keyword—Diabetes, DecisionTree, J48, C4.5, FBTree, Classification

"A Hybrid Classification Model For Diabetes Dataset Using Decision Tree", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.2, Issue 8, page no.3302-3308, August-2015, Available :http://www.jetir.org/papers/JETIR1508008.pdf

"A Hybrid Classification Model For Diabetes Dataset Using Decision Tree", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.2, Issue 8, page no. pp3302-3308, August-2015, Available at : http://www.jetir.org/papers/JETIR1508008.pdf