• Puneet Jain
• Priya Sen

Data Mining is used for various purposes in many applications like industries, medical, etc. This is used aimed at removing useful data after a huge quantity of data set. Health monitoring is also used in the data mining concept for predict analysis of the diseases. In health monitoring diabetes is the common health problem nowadays, which affects peoples. In this research, Pima Indians Diabetes Dataset, as well as Waikato Environment for Knowledge Analysis toolkit (WEKA), remained used to associate our consequences through consequences of the existing research work. In the previous research, three classification algorithms were used among which Naïve Bayes stand to be the most efficient one. But due to some limitations, Naïve Bayes is replaced by the Random Forest algorithm (RF). A comprehensive review of literature has been introduced which highlights the research operations using various data mining algorithms and tool as well. The assumption displays that the model achieved higher exactitude of prediction than that previous research.

data mining, diabetes data, chronic disease, WEKA, Random Forest

"Reducing the Risk of Diabetes Using Classification Technique in Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.230-233, June 2019, Available :http://www.jetir.org/papers/JETIR1907G78.pdf

"Reducing the Risk of Diabetes Using Classification Technique in Data Mining ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp230-233, June 2019, Available at : http://www.jetir.org/papers/JETIR1907G78.pdf