predict¶
-
Pipeline.
predict
(population_table, peripheral_tables=None, table_name='')[source]¶ Forecasts on new, unseen data using the trained
predictor
.Returns the predictions generated by the pipeline based on population_table and peripheral_tables or writes them into a data base named table_name.
- Args:
- population_table (
getml.data.DataFrame
): Main table corresponding to the
population
Placeholder
instance variable. Its target variable(s) will be ignored.- 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 toperipheral
.- table_name (str, optional):
If not an empty string, the resulting predictions will be written into the
database
of the same name. See Unified import interface for further information.
- population_table (
- 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:
numpy.ndarray
:Resulting predictions provided in an array of the (number of rows in population_table, number of targets in population_table).
- Note:
Only fitted pipelines (
fit()
) can be used for prediction.