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Evaluating Predictive Models

Evaluating Predictive Models

陈傲天
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In-sample, out-of-sample and generalization loss or error; risk as expected loss on new data. Under-fitting, over-fitting, and examples with polynomials. Methods of model selection and controlling over-fitting: empirical risk minimization, penalization, constraints/sieves, formal learning theory, cross-validation. Limits of generalization. R for creating figures.
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