Normalized

Normalized is the past participle of normalize. In general usage it describes something that has been converted to a standard or normal form, making it consistent or comparable. The concept appears across disciplines, where the aim is to reduce variation or complexity by applying a standard rule or scale.

In data processing and statistics: data normalization refers to scaling numeric values to a common range or distribution. Common methods include min-max normalization, which rescales to [0, 1], and z-score standardization, which centers data at zero with unit variance. Normalization can improve the performance of machine learning algorithms, facilitate comparison across datasets, and mitigate bias from differing units. In image processing, normalization often precedes analysis by adjusting pixel value ranges.

In database design, normalization is a methodological process to organize databases to reduce redundancy and improve data integrity. It involves structuring data into normal forms, such as 1NF, 2NF, 3NF, and BCNF, each with specific criteria. Normalization trades some performance for data consistency and flexibility; denormalization may be used for query speed. Spelling varies by region: normalization in American English and normalisation in British English.

In text processing, Unicode normalization standardizes different sequences of code points that render the same characters. Forms include NFC, NFD, NFKC, and NFKD, and are used to ensure consistent comparison, storage, and retrieval of text.