Summary
IEICE Information and Communication Technology Forum
2013
Session Number:COMM6
Session:
Number:COMM6-3
Boosting Committee Machines to Detect the Parkinson’s Disease by Neural Networks
Mehmet Can,
pp.-
Publication Date:2013-07-20
Online ISSN:2188-5079
Summary:
A boosting by filtering technique for neural network systems with back propagation together with a majority voting scheme is presented in this paper. Previous research with regards to predict the presence of Parkinson’s Disease has shown accuracy rates up to 92.9% but it comes with a cost of reduced prediction accuracy of the minority class. The designed neural network system boosted by filtering in this article presents a significant increase of robustness and it is shown that by majority voting of the parallel networks, recognition rates reach to > 90 in a imbalanced 3:1 imbalanced class distribution Parkinson’s Disease data set.