Gradient Learning Algorithm for Ensembling Neural Network
Meng Jiang, Kun An · 2006
Aimed at similarity between neural network ensemble and simple neural network, a novel gradient learning algorithm for ensemble (GLAENN) is presented based on the gradient descent method. The new algorithm can improve the generalization error by modifying subnet weights after the ensemble subnets are trained individually. The simulation results indicate GLAENN is of similar function to GASEN but with a different idea; further, it is of better generalization performance than GASEN, bagging and single network