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Comparison of Regularization Penalties Pt.2 Comparison of Regularization Penalties Pt.2

Comparison of Regularization Penalties Pt.2 - PowerPoint Presentation

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Uploaded On 2018-11-09

Comparison of Regularization Penalties Pt.2 - PPT Presentation

NCSU Statistical Learning Group Will Burton Oct 3 2014 The goal of regularization is to minimize some loss function commonly sum of squared errors while preventing Overfitting high variance low bias the model on the training data set ID: 724019

800 lasso 000 640 lasso 800 640 000 512 weight model grouped high 410 penalty data group predictors penalties

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