Inheritance diagram of Transformer
class evalml.pipelines.components.Transformer(parameters=None, component_obj=None, random_state=0, **kwargs)[source]

A component that may or may not need fitting that transforms data. These components are used before an estimator.

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 Transformer component.



Initialize self.


Constructs a new component with the same parameters


Describe a component and its parameters


Fits component to data


Fits on X and transforms X


Transforms data X