Allow custom Scikit params to be passed through in the advanced class about healthcareai-py HOT 3 CLOSED

@Aylr Said just confirmed that a dict can be passed for custom hyperparameter tuning

from healthcareai-py.

Great, I am happily mistaken! Sorry to underestimate!

from healthcareai-py.

Please see https://github.com/HealthCatalyst/healthcareai-py/blob/master/example_advanced.py and I'm happy to walk you a neat trick if this doesn't suffice!

Accessing the .advanced_features attribute on an instance of the SupervisedModelTrainer gives you the underlying advanced trainer. I routinely use this to mess with, say, random forest. For example: trainer.advanced_features.random_forest_classifier(hyperparameter_grid={stuff}) allows you the more control without giving up the goodness that SMT provides. Note you won't see graph output, so you'll have to make those plot calls.

from healthcareai-py.