score

Pipeline.score(population_table, peripheral_tables=None)[source]

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[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 id 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.