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 (List[getml.data.DataFrame]):

Additional tables corresponding to the peripheral Placeholder instance variable. They have to be passed in the exact same order as their corresponding placeholders! A single DataFrame will be wrapped into a list internally.

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).