Prediction of Neurological Disorder using Classification Approach
Abstract
Neurological disorder is the peculiar neurodegenerative diseases whose genuine reason for the explanation is as yet not clear to many peoples. The usage of classification methods in the neurological disorder can come about into proper characterization and prediction of subcortical structures of patients amid neurological disorder. Classification methods can be deployed to obtain suitable features from the brain morphometry data and calculate its performance in distinguishing between the health controls and patients diseased amid neurological disorder. This article deals with prediction of neurological disorder using classification approach. The results show that the KNN-MinMax classifier is exceptionally productive classifier for neurological disorder analysis which is around 6–8% more effective than the existing proposed methods.
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
This is an Open Access article distributed under the terms of the Attribution-Noncommercial 4.0 International License [CC BY-NC 4.0], which requires that reusers give credit to the creator. It allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, for noncommercial purposes only.