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add check for different scaler types

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Hannes Signer 2025-03-24 20:26:28 +01:00
parent dd1bdb7fc5
commit c7b89505c2
1 changed files with 6 additions and 0 deletions
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6
src/preprocessing.py
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@ -149,6 +149,11 @@ def custom_loss(
# as far as I know tensorflow does not directly support the use of scaler objects # as far as I know tensorflow does not directly support the use of scaler objects
# therefore, the backtransformation is done manually # therefore, the backtransformation is done manually
if preprocess.scaler_type != scaler_type:
raise Exception(
"Data normalized with scaler different than specified for the training. Compare the scaling approach on preprocessing and training.")
try: try:
if scaler_type == "minmax": if scaler_type == "minmax":
scale_X = tf.convert_to_tensor( scale_X = tf.convert_to_tensor(
@ -566,6 +571,7 @@ class preprocessing:
return design_resampled, target_resampled return design_resampled, target_resampled
def scale_fit(self, X, y, scaling, type="Standard"): def scale_fit(self, X, y, scaling, type="Standard"):
self.scaler_type = type
"""Fit a scaler for data preprocessing. """Fit a scaler for data preprocessing.
Args: Args: