Normalised: meaning, definitions and examples
✅
normalised
[ ˈnɔːr.mə.laɪzd ]
data processing
Normalized refers to the process of adjusting values in a dataset to a common scale, without distorting differences in the ranges of values. This is often done to improve comparability of data and is a widely used technique in statistics and data science.
Synonyms
adjust, equalize, standardize.
Examples of usage
- The data was normalized to improve analysis accuracy.
- In machine learning, we normally normalize our features before training.
- To compare the survey results, we need to normalize the scores.
condition description
When something is described as normalized, it means it has been made normal or standard. This can refer to systems, behaviors, or processes that have been adjusted to meet common standards or expectations.
Synonyms
Examples of usage
- The normalized conditions allowed for a fair comparison.
- Her normalized behavior made her more sociable.
- We expected the normalized rates to align with the previous year's data.
Translations
Translations of the word "normalised" in other languages:
🇵🇹 normalizado
🇮🇳 सामान्यीकृत
🇩🇪 normalisiert
🇮🇩 dinormalkan
🇺🇦 нормалізований
🇵🇱 znormalizowany
🇯🇵 正規化された
🇫🇷 normalisé
🇪🇸 normalizado
🇹🇷 normalleştirilmiş
🇰🇷 정규화된
🇸🇦 مُعَايَر
🇨🇿 normalizovaný
🇸🇰 normalizovaný
🇨🇳 标准化的
🇸🇮 normaliziran
🇮🇸 staðlaður
🇰🇿 нормаланған
🇬🇪 ნორმალიზებული
🇦🇿 normallaşdırılmış
🇲🇽 normalizado
Etymology
The term 'normalize' originates from the Latin word 'norma', meaning 'a carpenter's square' or 'a standard'. The use of 'normalize' emerged in the English language in the early 20th century, particularly within mathematical and statistical contexts. Originally, the concept involved standardizing measurement systems to ensure consistency and comparability. As fields such as economics, social sciences, and data analysis developed, normalization became crucial in processing and interpreting varied data sets. The prefix 'nor-' in 'normal' relates to the norm, which governs models and standards across disciplines, thus establishing a common framework within which disparity could be addressed and understood.