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| Scaler = preproc.MinMaxScaler | |
| normalizer_features = Scaler(copy=False) | |
| normalizer_features.fit_transform(features.reshape(num_sequences*num_timesteps, num_features)) | |
| normalizer_targets = Scaler(feature_range=(0, 1), copy=False) # sigmoid | |
| normalizer_targets.fit_transform(targets.reshape(num_sequences*num_timesteps, num_targets)) |
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