Build tool that automatically runs ML on model results, config, etc

Fit model performance on model characteristics (e.g. algorithm, hyperparameters, training window, other configurations). Helps identify what types of models do well during x time periods, etc.

No files, tests, or entry points are named. Start by reviewing the repository structure and existing model-result and configuration workflows, then clarify the intended inputs, evaluation target, and supported time-period analysis before defining what a complete implementation would include.

Written by the indexing model from the issue text.