Testing Ensemble Methods on Prediction of Protein Secondary Structure
نویسندگان
چکیده
The geometric opinion pool (GOP) ensemble method uses a multiplicative combination of predictors, and it is tailored to probability estimation in multi-class problems. This enables a decomposition of the KullbackLeibler entropy error function into an ambiguity term and an average error term. This can be used to estimate generalization error with a combination of cross-validation and estimation of ambiguity from unlabeled data. The method is tested empirically and found to compare favorably with single artificial neural networks, and ensemble methods using the linear opinion pool (LOP) and mean square error (MSE). The test problem is the prediction of secondary structure of proteins.
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