Regularised: meaning, definitions and examples
๐
regularised
[ หrษgjสlษraษชzd ]
mathematics, statistics
Regularised refers to the process of making something conform to a set of rules or standards. In mathematics and statistics, it often involves modifying an algorithm or model to prevent overfitting by adding additional constraints or penalties. This technique helps in improving the performance of predictive models. Regularisation is crucial in high-dimensional spaces, where models tend to capture noise instead of the underlying patterns.
Synonyms
constrained, normalised, standardised
Examples of usage
- We applied regularised regression to improve the model's accuracy.
- The data was regularised to ensure consistent results.
- He used a regularised version of the algorithm for better performance.
Translations
Translations of the word "regularised" in other languages:
๐ต๐น regularizado
๐ฎ๐ณ เคจเคฟเคฏเคฎเคฟเคค
๐ฉ๐ช reguliert
๐ฎ๐ฉ teratur
๐บ๐ฆ ัะตะณัะปััะธะทะพะฒะฐะฝะธะน
๐ต๐ฑ uregulowany
๐ฏ๐ต ่ฆๅๅใใใ
๐ซ๐ท rรฉgularisรฉ
๐ช๐ธ regularizado
๐น๐ท dรผzenlenmiล
๐ฐ๐ท ์ ๊ทํ๋
๐ธ๐ฆ ู ูุชุธู
๐จ๐ฟ regulovanรฝ
๐ธ๐ฐ regulovanรฝ
๐จ๐ณ ่ง่ๅ็
๐ธ๐ฎ urejen
๐ฎ๐ธ reglugeruรฐ
๐ฐ๐ฟ ัะตััะตะปะณะตะฝ
๐ฌ๐ช แ แแแฃแแแ แฃแแ
๐ฆ๐ฟ nizamlama
๐ฒ๐ฝ regularizado
Etymology
The term 'regularised' comes from the word 'regular', which has its roots in the Latin word 'regularis', meaning 'according to rule'. Initially used in various fields such as linguistics and geometry to describe things that adhere to a set standard, the concept of regularisation has evolved significantly, particularly in mathematics and statistics. In these fields, regularisation techniques were developed to tackle issues related to model complexity and predictions. Over time, the methodologies behind regularisation have become foundational in machine learning and statistical analysis, aiming to enhance model generalisation to unseen data by controlling for overfitting through added constraints. As data science has grown, so has the importance of regularised methods in ensuring robust and reliable models.
Word Frequency Rank
Ranking #36,307, this word is encountered relatively rarely in everyday English. It might appear in literary works or specialized texts but isn't essential for general communication.