An Efficient Diagnosis System for Parkinson’s Disease Using Kernel-Based Extreme Learning Machine with Subtractive Clustering Features Weighting Approach
Algorithm 2
Pseudocode for the proposed model.
Begin
Weight features using subtractive clustering algorithm;
For : k /*Performance estimation by using -fold CV, where /
Training set = k-1 subsets;
Test set = remaining subset;
Train KELM classifier in the weighted training data feature space, store the best parameter combination;
Test the trained KELM model on the test set using the achieved best parameter combination;
End For
Return the average classification results of KELM over th test set;
