from evalml.pipelines.components import ComponentBase
class Estimator(ComponentBase):
"""A component that fits and predicts given data"""
def predict(self, X):
"""Make predictions using selected features.
Args:
X (pd.DataFrame) : features
Returns:
pd.Series : estimated labels
"""
try:
return self._component_obj.predict(X)
except AttributeError:
raise RuntimeError("Estimator requires a predict method or a component_obj that implements predict")
def predict_proba(self, X):
"""Make probability estimates for labels.
Args:
X (pd.DataFrame) : features
Returns:
pd.DataFrame : probability estimates
"""
try:
return self._component_obj.predict_proba(X)
except AttributeError:
raise RuntimeError("Estimator requires a predict_proba method or a component_obj that implements predict_proba")
@property
def feature_importances(self):
try:
return self._component_obj.feature_importances_
except AttributeError:
raise RuntimeError("Estimator requires a feature_importances property or a component_obj that implements feature_importances_")