voiage.metamodels.EnsembleMetamodel
A metamodel that combines predictions from multiple metamodels.
Methods
Section titled “Methods”fit([positional or keyword] self: None = None, [positional or keyword] x: ParameterSet = None, [positional or keyword] y: np.ndarray = None) -> NoneFit all metamodels in the ensemble.
Parameters
Section titled “Parameters”x : ParameterSet The input parameters. y : np.ndarray The target values.
Parameters:
selfxParameterSetynp.ndarray
Returns: None
predict
Section titled “predict”predict([positional or keyword] self: None = None, [positional or keyword] x: ParameterSet = None) -> np.ndarrayPredict using the ensemble of metamodels.
Parameters
Section titled “Parameters”x : ParameterSet The input parameters.
Returns
Section titled “Returns”np.ndarray The ensemble predictions.
Parameters:
selfxParameterSet
Returns: np.ndarray
score([positional or keyword] self: None = None, [positional or keyword] x: ParameterSet = None, [positional or keyword] y: np.ndarray = None) -> floatReturn the coefficient of determination R^2 of the ensemble prediction.
Parameters
Section titled “Parameters”x : ParameterSet The input parameters. y : np.ndarray The true target values.
Returns
Section titled “Returns”float R^2 score of the ensemble.
Parameters:
selfxParameterSetynp.ndarray
Returns: float
rmse([positional or keyword] self: None = None, [positional or keyword] x: ParameterSet = None, [positional or keyword] y: np.ndarray = None) -> floatReturn the root mean squared error of the ensemble prediction.
Parameters
Section titled “Parameters”x : ParameterSet The input parameters. y : np.ndarray The true target values.
Returns
Section titled “Returns”float RMSE of the ensemble.
Parameters:
selfxParameterSetynp.ndarray
Returns: float