CONFUSION MATRIX ANALYSIS FOR EVALUATION OF SPEECH ON PARKINSON DISEASE USING WEKA AND MATLAB

ABSTRACT: A confusion matrix is a matrix for a two-class classifier, contains information about actual and predicted classifications done by a classification system. The accuracy obtained by training the probabilistic neural network using Parkinson disease dataset got 100% as positives, predictions that an instance is positive, using WEKA 3 and Matlab v7. Key words: Weka, Matlab, Parkinson disease. 1. INTRODUCTION Next to Alzheimer’s, Parkinson’s disease (PD) is the second most common neurodegenerative disorder 1 , and it is estimated that more 2than one million people in North America alone are affected . Rajput et al ., reported the incidence rates, have been approximately constant for the last 55 years, with 20/100,000 new cases every year 3 . A further estimated 20% of people with Parkinson’s (PWP) are never diagnosed 4 and are expected to increase because worldwide the population is growing older 5 . All major studies suggest age is the single most 6important risk factor for the onset of PD, which increases steeply after age fourty . There is no complete cure