evalml.pipelines.components.Estimator¶
-
class
evalml.pipelines.components.
Estimator
(parameters=None, component_obj=None, random_state=0, **kwargs)[source]¶ A component that fits and predicts given data.
To implement a new Transformer, define your own class which is a subclass of Transformer, including a name and a list of acceptable ranges for any parameters to be tuned during the automl search (hyperparameters). Define an __init__ method which sets up any necessary state and objects. Make sure your __init__ only uses standard keyword arguments and calls super().__init__() with a parameters dict. You may also override the fit, transform, fit_transform and other methods in this class if appropriate.
To see some examples, check out the definitions of any Estimator component.
Methods
Initialize self.
Constructs a new component with the same parameters
Describe a component and its parameters
Fits component to data
Make predictions using selected features.
Make probability estimates for labels.