Classification Of Diabetes Patients Using Kernel Based Support Vector Machines

Diabetes mellitus (DM) is a collection of metabolic diseases that influence the human pressure significantly worldwide. Detection of patient with diabetes at early stage is the most crucial task and helps to avoid the risk of the people from the diseases that lead to cause death. In diabetes research, the machine learning plays the important role in detecting the diseases at an early stage. There are more machine learning algorithms used for the research. Support Vector Machines (SVM) is the most successful and widely used algorithm. In this paper, SVM with different kernel functions are applied. SVM with linear kernel showed the highest accuracy value for the classification of diabetes.