hookeai.model_architectures.procedures.model_data_scaling

Procedures associated to model data scalers and scaling operations.

Functions

init_data_scalers

Initialize model data scalers.

set_data_scalers

Set fitted model data scalers.

set_fitted_data_scalers

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

fit_data_scalers

Fit model data scalers.

data_scaler_transform

Perform data scaling operation on features PyTorch tensor.

load_model_data_scalers_from_file

Load data scalers from model initialization file.

check_normalized_return

Check if model data normalization is available.

Functions

check_normalized_return(model)	Check if model data normalization is available.
data_scaler_transform(model, tensor, ...[, mode])	Perform data scaling operation on features PyTorch tensor.
fit_data_scaler_from_dataset(dataset, ...[, ...])	Fit features type data scaler from given data set.
fit_data_scalers(model, dataset[, ...])	Fit model data scalers.
get_fitted_data_scaler(model, features_type)	Get fitted model data scalers.
init_data_scalers(model)	Initialize model data scalers.
load_model_data_scalers_from_file(model)	Load data scalers from model initialization file.
set_data_scalers(model, scaler_features_in, ...)	Set fitted model data scalers.
set_fitted_data_scalers(model, scaling_type, ...)	Set fitted model data scalers from given scaler type and parameters.

Classes

TorchMinMaxScaler(n_features[, minimum, ...])	PyTorch tensor min-max data scaler.
TorchStandardScaler(n_features[, mean, std, ...])	PyTorch tensor standardization data scaler.