hookeai.model_architectures.procedures.model_data_scaling.set_fitted_data_scalers

set_fitted_data_scalers(model, scaling_type, scaling_parameters)

Set fitted model data scalers from given scaler type and parameters.

Parameters:

• model (torch.nn.Module) – Model.

• scaling_type ({'min-max', 'mean-std'}) – Type of data scaling. Min-Max scaling (‘min-max’) or standardization (‘mean-std’).

• scaling_parameters (dict) – Data scaling parameters (item, dict) for each features type (key, str). For ‘min-max’ data scaling, the parameters are the ‘minimum’ and ‘maximum’ features normalization tensors, as well as the ‘norm_minimum’ and ‘norm_maximum’ normalization bounds. For ‘mean-std’ data scaling, the parameters are the ‘mean’ and ‘std’ features normalization tensors.