Author : Prateek Mishra 1
Date of Publication :1st October 2020
Abstract: Diabetes may be a major disorder which may affect entire body system adversely. Undiagnosed diabetes can increase the danger of cardiac stroke, diabetic nephropathy and other disorders. everywhere the planet many people are suffering from this disease. Early detection of diabetes is extremely important to take care of a healthy life. This disease may be a reason of worldwide concern because the cases of diabetes are rising rapidly. Machine learning (ML) may be a computational method for automatic learning from experience and improves the performance to form more accurate predictions. within the current research we've utilized machine learning technique in Pima Indian diabetes dataset to develop trends and detect patterns with risk factors using R data manipulation tool. To classify the patients into diabetic and non-diabetic we've developed and analyzed five different predictive models using R data manipulation tool. For this purpose, we used supervised machine learning algorithms namely linear kernel support vector machine (SVM-linear), radial basis function (RBF) kernel support vector machine, k-nearest neighbor (k-NN), artificial neural network (ANN) and multifactor dimensionality reduction (MDR).
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