regularizer

regularizer : enum, adds a penalty to the weights to limit their growth and improve the model’s generalization.

Default

In default mode, you can choose between no regularization (default setting) or apply a predefined scheme: L1, L2, or L1L2.
In this configuration, the regularization coefficients l1 and l2 are fixed to 0.01 and cannot be modified.
This mode offers a simple way to introduce regularization without manually adjusting parameters.

L1

L1 regularization adds a penalty proportional to the absolute values of the weights:

This promotes sparsity by encouraging weights to become exactly zero.
When selected explicitly, the l1 coefficient can be set freely.

L2

L2 regularization adds a penalty proportional to the squared values of the weights:

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This helps prevent overfitting by discouraging large weights and smoothing the model.
The l2 coefficient is user-configurable when this mode is selected.

L1L2

L1L2 combines both L1 and L2 penalties:

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It balances sparsity (from L1) and weight decay (from L2), offering finer control over the regularization behavior.
Both l1 and l2 coefficients are available for customization in this mode.