Hyperparameter optimization
From Rice Wiki
Aspects of an ML model is controlled by hyperparameters. Hyperparameter optimization is an iterative process that attempts to find the best hyperparameters for a given model.
Grid search
Grid search (aka. grid search cross validation) computes all possible combinations of hyperparameters based on your input (possible values for each hyperparameter). The model is then trained and validated, and the best performance result is taken.
Other techniques
Other techniques include
- Random search: faster but no guarantee
- Bayesian optimizaiton
- Hyperband
