Model retraining using recipes¶
This page describes how to retrain a model using recipes.
To avoid any extra auto-generated individuals for refit or retrained experiments with a custom individual, set
fixed_num_individuals equal to the desired number of custom individuals in the final model. Also, ensure that
enable_genetic_algorithm is set to
Additionally, you can set the following parameters to prevent the mutation of the genome for this individual (frozen case), in self.params dictionary in Individual Recipe’s
prob_add_genes = 0.0 prob_prune_genes = 0.0 prob_prune_by_features = 0.0 prob_addbest_genes = 0.0 prob_prune_by_top_features = 0.0
Also, uncomment the following code in the Individual Recipe’s
Note that the validation scores can have some randomness, but when the parent experiment has a reproducible level set with the relevant reproducible levels, the test scores should match.