@inbook{859694d72851402c8fce7ec3d56f9bd5,
title = "Large ensemble averaging",
abstract = "Averaging over many predictors leads to a reduction of the variance portion of the error. We present a method for evaluating the mean squared error of an infinite ensemble of predictors from finite (small size) ensemble information. We demonstrate it on ensembles of networks with different initial choices of synaptic weights. We find that the optimal stopping criterion for large ensembles occurs later in training time than for single networks. We test our method on the suspots data set and obtain excellent results.",
author = "David Horn and Ury Naftaly and Nathan Intrator",
year = "2012",
doi = "10.1007/978-3-642-35289-8_9",
language = "אנגלית",
isbn = "9783642352881",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "131--137",
booktitle = "Neural Networks",
}