International Journal of Advanced Innovative Technology in Engineering (IJAITE)

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Detection of Parkinson’s Disease By Using Matlab

AKASH P. MANWATKAR, PROF. S. R. SALWE, DR. R. D. RAUT

Abstract :

This paper present different method of diagnosis of Parkinson’s disease through voice in early stages. The aim of this study is to provide a simple, fast, cheaper method of detection of Parkinson’s disease for the patients as there is no cure for this disease and the available therapies which provide some relief to them are too much costlier for this disease. We used Linear and Non-linear kernel function together for improving the accuracy of the Support Vector Machines (SVMs) classification. We have used kernel function with a number of parameters associated with the use of the SVM algorithm that can impact the results. A comparative analysis of Linear SVM versus Non-linear SVMs for data classifications is also presented to verify the effectiveness of the kernel function. We seek an answer to the question: ‘‘which kernel can achieve a highest accuracy classification among all kernel functions’’. The support vector machines are evaluated in comparisons with different kernel functions by application to a variety of non-separable data sets with several attributes.

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