fit

GaussianHyperparameterSearch.fit(population_table_training, population_table_validation, peripheral_tables=None)

Launches the hyperparameter optimization.

The provided DataFrame population_table_training, population_table_validation and peripheral_tables must be consistent with the Placeholders provided when constructing the base model.

Args:

population_table_training(DataFrame):

The population table that pipelines will be trained on.

population_table_validation(DataFrame):

The population table that pipelines will be evaluated on.

peripheral_tables(DataFrame): The

peripheral tables used to provide additional information for the population tables.

Raises:

TypeError: If any of population_table_training,

population_table_validation or peripheral_tables is not of type DataFrame.

KeyError: If an unsupported instance variable is

encountered (via validate()).

TypeError: If any instance variable is of wrong type (via

validate()).

ValueError: If any instance variable does not match its

possible choices (string) or is out of the expected bounds (numerical) (via validate()).