DIABETES PREDICTION USING MACHINE LEARNING

DIABETES PREDICTION USING MACHINE LEARNING

Ms.M.Santhy  Computer Science and Engineering & Dhirajlal Gandhi College of Technology

Mr.M.Mohana Priyan  Computer Science and Engineering & Dhirajlal Gandhi College of Technology

Mr.M.Syedabuthahir  Computer Science and Engineering & Dhirajlal Gandhi College of Technology

Mr.S.Tamilarasan  Computer Science and Engineering & Dhirajlal Gandhi College of Technology

Mr.S.Tamilselvan  Computer Science and Engineering & Dhirajlal Gandhi College of Technology

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Abstract - Diabetes is a serious disease that affects the majority of the population. It is caused due to increased blood sugar level because of imbalance in insulin processing by the body. Machine learning is an emerging scientific field in data science dealing with the ways in which machines learn from experience. The aim of this work is to make an early prediction of diabetes more precisely by using a variety of machine learning algorithms. Machine learning algorithms provide better results in diabetes prediction by constructing models from patient datasets. This project has incorporated the algorithms like Naive Bayes, K-Nearest Neighbor (KNN), Logistic Regression, Random Forest, Support Vector Machine (SVM), Decision Tree, Multi-Layer perceptron (MLP) and Logistic Model Tree (LMT). The accuracy is different for all of them.

Key Words:  Machine learning, Naive Bayes, K-Nearest Neighbor, Logistic Regression, Random Forest, Support Vector Machine, Decision Tree, Multi-Layer perceptron and Logistic Model Tree.