منابع مشابه
Optimal Linear Regression on Classi
We consider the combination of the outputs of several clas-siiers trained independently for the same discrimination task. We introduce new results which provide optimal solutions in the case of linear combinations. We compare our solutions to existing ensemble methods and characterize situations where our approach should be preferred.
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Expressions are derived for generalized ridge and ordinary ridge predictors that are optimal in terms of mean squared error of prediction (MSEP) for predicting the response at a single or at multiple future observation(s). Using the MSEP criterion, operational predictors are compared to the ordinary least squares (OLS) predictor and to several biased predictors derived from some popular biased ...
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Authors are encouraged to submit new papers to INFORMS journals by means of a style file template, which includes the journal title. However, use of a template does not certify that the paper has been accepted for publication in the named journal. INFORMS journal templates are for the exclusive purpose of submitting to an INFORMS journal and should not be used to distribute the papers in print ...
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We consider the combination of the outputs of several classifiers trained independently for the same discrimination task. We introduce new results which provide optimal solutions in the case of linear combinations. We compare our solutions to existing ensemble methods and characterize situations where our approach should be preferred.
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ژورنال
عنوان ژورنال: Stats
سال: 2019
ISSN: 2571-905X
DOI: 10.3390/stats2040028