Module preprocessing 

Feature preprocessing transformers.

All transformers maintain per-feature online statistics and use O(d) memory where d is the feature dimension.

Re-exports

pub use clipper::Clipper;

pub use constant_imputer::ConstantImputer;

pub use constant_imputer::ConstantImputerConfig;

pub use forward_fill::ForwardFill;

pub use frequency::FrequencyEncoder;

pub use mean_imputer::MeanImputer;

pub use min_max_scaler::MinMaxScaler;

pub use missing_indicator::MissingIndicator;

pub use one_hot::OneHotEncoder;

pub use ordinal::OrdinalEncoder;

pub use standard_scaler::StandardScaler;

pub use standard_scaler::StandardScalerConfig;

Modules

clipper

Feature clipper.

constant_imputer

Constant value imputer for missing data.

forward_fill

Forward-fill imputer for missing data.

frequency

Online frequency encoder for categorical string features.

mean_imputer

Mean imputer for missing data.

min_max_scaler

Online min-max scaler.

missing_indicator

Missing value indicator transformer.

one_hot

Online one-hot encoder for categorical string features.

ordinal

Online ordinal encoder for categorical string features.

standard_scaler

Online standard scaler.