fair_forge.split¶

Classes

SplitMethod(…)

Protocol for split methods.

Functions

`basic_split`(seed, train_percentage, *, ...)	Split the dataset into training and testing sets with a basic split.
`proportional_split`(seed, train_percentage, ...)	Generate the indices of the train and test splits using a proportional sampling scheme.

class fair_forge.split.SplitMethod(*args, **kwargs)[source]¶

Bases: Protocol

Protocol for split methods.

fair_forge.split.basic_split(seed: int, train_percentage: float, *, target: ndarray[tuple[Any, ...], dtype[int32]], groups: ndarray[tuple[Any, ...], dtype[int32]]) → tuple[ndarray[tuple[Any, ...], dtype[int64]], ndarray[tuple[Any, ...], dtype[int64]]][source]¶: Split the dataset into training and testing sets with a basic split.

fair_forge.split.proportional_split(seed: int, train_percentage: float, *, target: ndarray[tuple[Any, ...], dtype[int32]], groups: ndarray[tuple[Any, ...], dtype[int32]]) → tuple[ndarray[tuple[Any, ...], dtype[int64]], ndarray[tuple[Any, ...], dtype[int64]]][source]¶: Generate the indices of the train and test splits using a proportional sampling scheme.