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Results tagged with regularization
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user 82467
Inclusion of additional constraints (typically a penalty for complexity) in the model fitting process. Used to prevent overfitting / enhance predictive accuracy.
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Is the regularization term necessary when classifying one feature?
R is the regularization term (penalty):
$$\omega = \omega - \eta \left[ \alpha \frac{\partial R(\omega)}{\partial \omega} + \frac{\partial L(\omega^T x_i + b, y_i)}{\partial \omega} \right]$$
After trying … to alter some of the most basic parameters of this classifier (loss function, max_iters), I started wondering if in this case where the dataset has only one feature, whether it is necessary to add a regularization …
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