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

Calculates the performance of the predictor.

Returns different scores calculated on population_table and peripheral_tables.

population_table (

Main table corresponding to the population Placeholder instance variable.

peripheral_tables (Union[List[], dict,]):

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.

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


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).



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


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