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(True, False) 7. Cross-validation procedure is usually applied to estimate bias and variance.

(True, False) 7. Cross-validation procedure is usually applied to estimate bias and variance.

Math   Statistics-And-Probability   
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Answer #1

Yes it's true.

Cross validation procedure is usually applied to estimate bias and variance.

The main goal of cross-validation is to test how well the model is able to predict new data that was not used in estimating it. It helps to find out the trade off between bias and variance. A good model is that for which neither bias nor variance is too large. So we try to find bias and variance such the model predictive performance is good on new ( independent) dataset.

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