score

Pipeline.score(population_table, peripheral_tables=None)

Calculates the performance of the predictor.

Returns different scores calculated on population_table and peripheral_tables.

Args:

population_table (getml.data.DataFrame):

Main table corresponding to the population Placeholder instance variable.

peripheral_tables (

Union[getml.data.DataFrame, List[getml.data.DataFrame], dict]): Additional tables corresponding to the peripheral Placeholder instance variable. They have to be provided 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. ValueError: If no valid predictor was set. 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).

Return:

dict:

Mapping of the name of the score (str) to the corresponding value (float).

For regression problems the following scores are returned:

• rmse

• mae

• rsquared

For classification problems the following scores are returned:

• accuracy

• auc

• cross_entropy

Note:

Only fitted pipelines (fit()) can be scored.