• Mahesh Kumar
• Krishan Kumar Sharma
• Deepak Moud

Diabetes is a tireless and hazardous ailment, which is a gathering of metabolic issue portrayed by high glucose levels over an extensive stretch. This can prompt numerous issues if not treated and recognized. Common work to recognize the procedure of diabetes includes numerous means from visiting specialists to numerous demonstrative tests, however AI innovation can be helpful for taking care of this issue. The reason for this article is to analyze the four calculations and build up a model to anticipate the probability of diabetes in patients with greatest precision. Along these lines, this test utilizes four programmed learning order calculations: credulous Bayesian, irregular backwoods, straight relapse and strategic relapse to quantify the precision of different calculations and decide the event of a malady from these outcomes. The examinations are led in the Indian Pima Database for Diabetes (PIDD), which is gotten from the UCI archive of AI databases

Diabetes; SVMa,Naive Byesa,Decision Tree, Accuracya, Machine Learning

" COMPARATIVE ANALYSIS OF SUPERVISED LEARNING ALGORITHM IN DIABETES DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.144-147, May-2019, Available :http://www.jetir.org/papers/JETIRBW06030.pdf

" COMPARATIVE ANALYSIS OF SUPERVISED LEARNING ALGORITHM IN DIABETES DETECTION", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp144-147, May-2019, Available at : http://www.jetir.org/papers/JETIRBW06030.pdf