feat: add support for none to indicate no regularization - #13672
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kgryte
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kgryte
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kgryte
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kgryte
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Co-authored-by: Athan <kgryte@gmail.com> Signed-off-by: Athan <kgryte@gmail.com>
kgryte
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| - **STDLIB_ML_SGD_CLASSIFICATION_ELASTICNET**: regularization method that linearly combines the L1 and L2 penalties of the lasso and ridge methods. | ||
| - **STDLIB_ML_SGD_CLASSIFICATION_L1**: L1 regularization (also called LASSO) leads to sparse models by adding a penalty based on the absolute value of coefficients. | ||
| - **STDLIB_ML_SGD_CLASSIFICATION_L2**: L2 regularization (also called ridge regression) encourages smaller, more evenly distributed weights by adding a penalty based on the square of the coefficients. | ||
| - **STDLIB_ML_SGD_CLASSIFICATION_NONE**: no regularization. |
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This naming convention is a bit risky insofar as this doesn't clash with any other enum belonging to other parameterizations (e.g., loss functions, learning rates, etc).
Fine to leave as is for now. Otherwise, we may need to update our conventions if this assumption is invalidated in the future.
none value for penalties enumnone to indicate no regularization
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Resolves #None.
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nonevalue forpenaltiesenum.Related Issues
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