Normaliserte

Normaliserte is the past participle form of the Norwegian verb normalisere and is used to describe data, measurements or structures that have undergone normalization. Normalization is the process of adjusting values measured on different scales to a common scale, or transforming distributions to a standard form, often to improve comparability, numerical stability, or compliance with model assumptions.

Common normalization techniques include min–max normalization, which rescales values to a fixed range such as 0 to 1; standardization (z-scores), which centers data at zero and scales to unit variance; and vector normalization, which scales vectors to unit length. For skewed distributions, log transformations or robust scaling may be applied to reduce the influence of outliers.

Applications span statistics, machine learning, data preprocessing and database design. In machine learning, normalizing features can improve convergence and performance for algorithms that rely on scale, such as gradient-based methods. In relational databases, normalization refers to organizing data to reduce redundancy and improve integrity, which can produce 'normaliserte' datasets under a given normal form.

Choosing a normalization method depends on the data and the intended use; inappropriate normalization can distort interpretability or the effects of outliers. The term 'normaliserte' thus signals that the values have been transformed to a standard scale or form.