Prediction of Parkinson's Disease Using Feature Optimization and Classification

Categorization has been significant field for researchers. It deals with the categorization of items using various techniques such as soft computing, machine learning, deep learning etc. Grouping images on the basis of their properties is termed as Image Classification. Image classification is important filed of research for medical, industrial, scientific and real world applications. A standard dataset of Parkinson's disease is attained from UCI and Hybrid approach of optimization and classification is applied. Optimization algorithm is used to minimize the dimensionality of dataset and classification technique is applied on reduced data set.