What does regularization mean?
Regularization is the process of making something follow a consistent pattern, standard rule, or orderly system. It can describe administrative measures that standardize procedures, as well as mathematical techniques that extend a rule to previously untreated cases. In statistics and machine learning, regularization introduces a constraint or penalty to prevent a model from becoming overly complex and fitting random fluctuations in the training data. The word is therefore associated with order, consistency, and controlled generalization, although the technical meanings are more specific than the general one. It is especially useful in discussions of mathematics, data preparation, and machine learning, where an unregularized model may produce unstable or excessively tailored results.
nounThe act or process of making something regular, consistent, or systematic. In mathematics and related fields, it may refer specifically to extending a rule or formula to a broader set of cases.
- The process of making something regular, consistent, or systematic.
- In mathematics, the extension of a rule or formula to cases where it did not initially apply.
- In statistics and machine learning, a method used to reduce overfitting by adding a penalty or constraint to a model.
"The regularization of the data helped remove inconsistencies before the analysis."
"The library introduced a regularization program to make its records easier to search."
"Ridge regularization reduced the model's tendency to fit the training data too closely."
Plural forms are used when referring to multiple distinct processes or instances of making something regular.
"The study compares several regularizations of the same statistical model."
In machine learning, regularization is like adding guardrails to a model, discouraging it from memorizing noise instead of learning the pattern.
Reviewed by Deb Chak, Editor. AI-assisted content curated by RJS Tech Solutions LLP.
Where does regularization come from?
Regularization was formed in English by combining regular with the suffix -ization. Regular ultimately comes through Old French from Latin regularis, meaning “according to rule,” while -ization was borrowed from French and ultimately reflects Greek-forming elements associated with -izein, “to make like.” The resulting word has developed into both a general term for making practices consistent and a specialized term in mathematics, statistics, and machine learning.
Related word forms
How regularization is actually used
The term is most common in academic, technical, and administrative contexts. In mathematics and data science, it usually has a specialized technical meaning; in general usage, it can sound formal.
Easily confused with regularization
Regularization is the process of making something regular or consistent, whereas a regulation is an official rule or set of governing requirements.