evalml.pipelines.components.Transformer

class evalml.pipelines.components.Transformer(parameters=None, component_obj=None, random_seed=0, **kwargs)

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.

Methods

__init__	Initialize self.
clone	Constructs a new component with the same parameters and random state.
describe	Describe a component and its parameters
fit	Fits component to data
fit_transform	Fits on X and transforms X
load	Loads component at file path
save	Saves component at file path
transform	Transforms data X.

Class Inheritance

evalml.pipelines.components.ComponentBase.save evalml.pipelines.components.Transformer.__init__