Your History

Menu

General Form of a Regularization Function

Description

To facilitate finding simpler prediction models, a regularization function is typically used. This can factor several types of model complexity, such as the magnitude of the parameters, and penalize models that are too complex. A typical example is the L2 Regularization. Regularization is used as a form of overfitting prevention.

\[\htmlClass{sdt-0000000076}{\textup{reg}} : \htmlClass{sdt-0000000052}{\Theta} \rightarrow \htmlClass{sdt-0000000045}{\mathbb{R}}_{\geq 0}\]

Symbols Used:

This is the symbol used for representing a regularization function.
\( \mathbb{R} \)

This is the symbol for the set of real numbers.
\( \Theta \)

This is the symbol for the set of all possible model parameters \( \htmlClass{sdt-0000000066}{\theta} \).

Example

Examples of Common Regularization Functions:

  1. L2 Regularization

References

Jaeger, H. (n.d.). Neural Networks (AI) (WBAI028-05) Lecture Notes BSc program in Artificial Intelligence. Retrieved April 24, 2024, from https://www.ai.rug.nl/minds/uploads/LN_NN_RUG.pdf