Feature Selection Techniques for Prediction of Neuro-Degenerative Disorders: A Case-Study with Alzheimer’s And Parkinson’s Disease

Abstract

Alzheimer’s and Parkinson’s disease are the most common forms of dementia that degenerate neurons in the brain cells. This paper targets a comparative study on the performance of data mining techniques in neuro-degenerative data. The existing data mining algorithms give classification accuracy ~93% with Correlation-based feature subset selection method. The proposed Decremental Feature Selection Method has yielded a more optimal feature subset that gives higher accuracy in prediction. Further exploration of computational methods to investigate the role of such genetic variants will aid in identifying the genetic cause of these diseases and design suitable drugs to target the gene property.