Some traditional and nontraditional features are analyzed for the parkinson disease classification. Various classifiers are used for this purpose. Parkinson voice has tremor in it and it is visible in jitter and shimmer values.Jitter values are higher in parkinson subjects than the healthy one. Same results are observed in case of shimmer.The harmonic to noise ratio values are high for the healthy one. The non-traditional measures show appreciable differentiation between the two classes. All the three features DFA, Spread1 and PPE have higher values for parkinson subjects than the healthy one. The tansig transfer function neural network