Weighted ensemble based on 0-1 matrix decomposition

A simple effective ensemble method is proposed in which individual classifiers are combined with the weight coefficients obtained by decomposition for the 0-1 matrix. The 0-1 matrix is introduced to denote individual classifiers of the ensemble and is constructed based on the prediction labels of individuals and the true labels. The weight coefficients of individuals are obtained by singular value decomposition for the 0-1 matrix based on linear mapping. In particular, the square of elements of the right singular vector corresponding to the maximum singular value are as the weight coefficients of individuals, and it is proved theoretically that it minimises the upper bound of ensemble error. Experimental results illustrate that the proposed method improves the performance of classification compared against standard ensemble strategies.