Weighted least square ensemble networks

From the result, it is found that for the correlation ensemble, one variance of the weighted least square method gave the best ensemble weightings.

Abstract

Ensemble of networks has been proven to give better prediction result than a single network. Two commonly used methods of determining the ensemble weights are simple average ensemble method and the generalized ensemble method. In the paper, we propose a weighted least square ensemble network. The major difference between this method and the other ensemble methods is that we do not assume that neither individual training data nor networks in the ensemble are independent and uncorrelated. Two variances of this model are also introduced, which require fewer computations. The sunspot data was used as a benchmark test of the proposed methods. From the result, we find that for the correlation ensemble, one variance of the weighted least square method gave the best ensemble weightings.