• Gavin Pinto
• Sunil Jangid
• Radhika Desai

Data mining techniques explore critical information in various domains (for example in CRM (customer relationship management), HR (Human Resource), GIS (Geographic Information System) etc.) but most importantly in medical domain. In medical domain, data mining can assist on minimizing the risk of developing some of the stereotyped diseases such as cancer, heart diseases, diabetes etc. Diabetes is considered as one of the deadliest and chronic diseases which causes an increase in blood sugar. Many complications occur if diabetes remains untreated or unidentified. The tedious identifying process results in visiting of a patient to a diagnostic center and consulting doctor. But the rise in machine learning approaches solves all this critical problem. The motive of this study is to design a website which can give a probability of having diabetes depending upon the information user is entering and giving a prediction of if the person is prone to having diabetes in the near future. Therefore, two machine learning classification algorithms namely SVM and Naive Bayes are used in this experiment to detect diabetes at an early stage. Experiments are performed on a dataset collected by a google form survey. The performances of all the algorithms are evaluated on various measures like Precision and Accuracy. Accuracy is measured over correctly and incorrectly on classified instances. Results obtained show Naive Bayes outperforms with the highest accuracy of 60.30% comparatively other algorithms.

Data Mining, Blood Pressure, Naive Bayes, SVM

"Understanding the Lifestyle of People to Identify the Reasons of Diabetes Using Data Mining", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.441-445, June-2019, Available :http://www.jetir.org/papers/JETIR1906501.pdf

"Understanding the Lifestyle of People to Identify the Reasons of Diabetes Using 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. pp441-445, June-2019, Available at : http://www.jetir.org/papers/JETIR1906501.pdf