ADAPTIVE COMMITTEES OF NEURAL CLASSIFIERS
It is obvious that combination of several classifiers might improve overall classification performance. In this paper, on the contrary to the ordinary approach of utilising all neural networks available to make the committee decision, we propose to create adaptive committees, which are specific for each input data point. A prediction neural network is used to identify classifiers to be fused for making a committee decision about the given input data. The proposed technique is tested in three aggregation schemes and the effectiveness of the approach is demonstrated on the three real data sets.
adaptive committees neural networks aggregation half&half sampling