evalml.pipelines.components.Transformer

class evalml.pipelines.components.Transformer(parameters=None, component_obj=None, random_seed=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.

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

Inheritance diagram of Transformer