Balancing Between Bagging and Bumping

  title={Balancing Between Bagging and Bumping},
  author={Tom Heskes},
We compare different methods to combine predictions from neural networks trained on different bootstrap samples of a regression problem. One of these methods, introduced in [6] and which we here call balancing, is based on the analysis of the ensemble generalization error into an ambiguity term and a term incorporating generalization performances of individual networks. We show how to estimate these individual errors from the residuals on validation patterns. Weighting factors for the different… CONTINUE READING
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An Introduction to the Bootstrap

  • B. Efron, R. Tibshirani
  • Chapman & Hall, London
  • 1993
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