Neural network ensembles

@article{hansen_1990_ieeetpami, abstract = {Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and architecture. It is shown that the remaining residual generalization error can be reduced by invoking ensembles of similar networks}, author = {Hansen, L. K. and Salamon, P. }, citeulike-article-id = {816658}, doi = {10.1109/34.58871}, journal = {Pattern Analysis and Machine Intelligence, IEEE Transactions on}, keywords = {classifier\_ensemble}, number = {10}, pages = {993--1001}, posted-at = {2008-02-26 18:38:14}, priority = {0}, title = {Neural network ensembles}, url = {http://dx.doi.org/10.1109/34.58871}, volume = {12}, year = {1990} }

TY - JOUR ID - hansen_1990_ieeetpami L3 - citeulike-article-id:816658 TI - Neural network ensembles JF - Pattern Analysis and Machine Intelligence, IEEE Transactions on VL - 12 IS - 10 SP - 993 EP - 1001 N2 - Several means for improving the performance and training of neural networks for classification are proposed. Crossvalidation is used as a tool for optimizing network parameters and architecture. It is shown that the remaining residual generalization error can be reduced by invoking ensembles of similar networks KW - classifier_ensemble AU - Hansen, LK AU - Salamon, P PY - 1990/// UR - http://dx.doi.org/10.1109/34.58871 ER -