Table of Contents

Namespace AiDotNet.Preprocessing.Scalers

Classes

DecimalScaler<T>

Scales features by dividing by the smallest power of 10 greater than the max absolute value.

GlobalContrastScaler<T>

Scales features by adjusting contrast based on mean and standard deviation.

LogMeanVarianceScaler<T>

Applies logarithmic transformation followed by mean-variance standardization.

LogScaler<T>

Applies logarithmic transformation to features, useful for data spanning multiple orders of magnitude.

MaxAbsScaler<T>

Scales each feature by its maximum absolute value.

MinMaxScaler<T>

Scales features to a given range, typically [0, 1].

Normalizer<T>

Normalizes samples (rows) individually to unit norm (L1, L2, or Max).

RobustScaler<T>

Scales features using statistics that are robust to outliers.

StandardScaler<T>

Standardizes features by removing the mean and scaling to unit variance.

Enums

NormType

Specifies the norm to use for sample normalization.