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| # Usage | |
| In this visualizer, you visualize the loss and regularization of linear regression models on a given dataset. | |
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| ### Data | |
| In the data tab, select a predefined regression dataset, or choose **Custom** to generate a dataset using a custom function or upload a CSV file. Predefined datasets have standardized covariates and a centered target. Make sure the function depends on `x1` and `x2`. | |
| ### Regularization | |
| Select your loss function and regularization type. Set the regularization level range as two comma-separated values (for example, `0.001, 50`). | |
| ### Generating plots | |
| Click **Regenerate Plots** to update plots with the current settings | |
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| ### Contour Plot | |
| The contour plot shows the loss values and the regularization norms for the linear models on the dataset. The red path shows how the loss and regularization norm values | |
| change across the selected regularization level range. You can see that the path intersects where the loss and regularization contours are parallel. | |
| ### Data Plot | |
| The data plot shows the data points used to compute the loss values. | |
| ### Regularization path plot | |
| The regularization path plot shows regularization strength versus coefficient value for every covariate. Datasets with more than two covariates show only this plot. These match the values shown on the red regularization path in the contour plot. | |