File:Optimalalpha.png
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Captions
Captions
Cross-validated Mean Squared Error (MSE) of Lasso Regression across different regularization strengths (α)
Summary[edit]
| Description |
English: The figure displays the relationship between the regularization strength (α) and the Mean Squared Error (MSE) for a Lasso Regression model using 5-fold cross-validation. The shaded region around the mean MSE curve represents the variability in the MSE across the folds, measured as one standard deviation. As α increases, representing stronger regularization, the model becomes sparser, selecting fewer features. The red dashed line indicates the optimal α value of approximately 0.3594, which minimizes the cross-validated MSE. Balance between fitting the training data and generalizing to new data. |
| Date | |
| Source | Own work |
| Author | Chamaemelum |
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| Date/Time | Thumbnail | Dimensions | User | Comment | |
|---|---|---|---|---|---|
| current | 22:45, 25 August 2023 | | 1,686 × 1,103 (121 KB) | Chamaemelum (talk | contribs) | Uploaded own work with UploadWizard |
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