AN improved ensemble appraoch with Probabilistic Neural Network-Combinational algorithm
The Combinational algorithm in the ensemble approach plays a key role towards the performance. The standard majority voting, weighted average and probabilistic averaged weight could not tune well the decisions of the multi-classifiers to the class label. We propose the modeling of the multi-classifier decisions to the output variable using Probabilistic Neural Networks as the combinational algorithm. This proposed implementation of combinational algorithm gave a significant performance improvement against the standard combiners.