fit

Pipeline.fit(population_table, peripheral_tables=None)

Trains the feature learning algorithms, feature selectors and predictors.

Args:

population_table (getml.data.DataFrame):

Main table containing the target variable(s) and corresponding to the population Placeholder instance variable.

peripheral_tables (Union[List[getml.data.DataFrame], dict, getml.data.DataFrame]):

Additional tables corresponding to the peripheral Placeholder instance variable. If passed as a list, the order needs to match the order of the corresponding placeholders passed to peripheral.

Raises:

IOError: If the pipeline corresponding to the instance

variable name could not be found on the engine or the pipeline could not be fitted.

TypeError: If any input argument is not of proper type.

KeyError: If an unsupported instance variable is

encountered.

TypeError: If any instance variable is of wrong type.

ValueError: If any instance variable does not match its

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