commonpower.data_forecasting.nn_forecasting.transform.SklearnScalerTransform

class SklearnScalerTransform(scaler: Any)[source]

Bases: Transformation

Transformation based on a sklearn scaler. We need the given scaler to implement fit(), transform() and inverse_transform() methods. Caution regarding the state_dict() and load_state_dict() methods: Some exotic scalers might need a custom implementation. :param scaler: Instance of sklearn scaler. :type scaler: Any, optional

Methods

`fit`	Fit the transformation to the data.
`from_checkpoint`
`inverse`	Inverse transform the data.
`load_state_dict`	Load the state of the transformation.
`state_dict`	Return the state of the transformation.

__call__(data: ndarray) → ndarray[source]: Transform the data.

fit(data: ndarray)[source]: Fit the transformation to the data.

inverse(data: ndarray) → ndarray[source]: Inverse transform the data.

load_state_dict(state_dict: dict) → None[source]: Load the state of the transformation.

state_dict() → dict[source]: Return the state of the transformation.