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Media type:
E-Article
Title:
A Comparison of Some Error Estimates for Neural Network Models
Contributor:
Tibshirani, Robert
imprint:
MIT Press - Journals, 1996
Published in:Neural Computation
Language:
English
DOI:
10.1162/neco.1996.8.1.152
ISSN:
0899-7667;
1530-888X
Origination:
Footnote:
Description:
<jats:p> We discuss a number of methods for estimating the standard error of predicted values from a multilayer perceptron. These methods include the delta method based on the Hessian, bootstrap estimators, and the “sandwich” estimator. The methods are described and compared in a number of examples. We find that the bootstrap methods perform best, partly because they capture variability due to the choice of starting weights. </jats:p>