Add Parameter Scaling Options
@cssherman is already working on this.
Since Jul 27, 2026.
- Dominant language
- Python
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Description
Professor does not make any assumptions about the scaling of input parameters and output fields, which can cause problems during model training if their distributions vary significantly. Add an option to normalize values and improve the model learning rate / stability.
To achieve this, add a new user-facing option to prof-trainer called "scaling", which has the following options:
- none (default): Do not apply scaling to the dataset
- auto: Inspect the dataset before training and estimate the required scaling parameters
- filename: Read in pre-computed scaling parameters from a yaml format file
To validate the new option, do the following:
- Create a test dataset that has poorly scaled input parameters
- Compare model performance for both cases
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