Glossary
- Nested Fitting Procedure
- Hyperparameter Optimization
A two-level fitting procedure that optimises hyperparameters and learned parameter by iteratively retraining the model and validating it against performance constraint.
- Training Configuration
A file that defines the initial model and training parameters for either training or the nested fitting procedure. It completely specifies the initialise model.
- Nested Fitting Configuration
- HPO Configuration
A file that defines the settings used for nested fitting procedure.
- Hyperparameter
A model parameter chosen before regression (cutoff, number of Gaussians …).
- Learned Parameter
Coefficient found by regression (\(\mathbf w\)).
- Performance constraint
A measurable (physical) property used as part of the loss.
- Search Space Constraint
A bound placed on a hyperparameter via an
OPTIMline.