evalml.pipelines.components.RFRegressorSelectFromModel

class evalml.pipelines.components.RFRegressorSelectFromModel(number_features=None, n_estimators=10, max_depth=None, percent_features=0.5, threshold=- inf, n_jobs=- 1, random_state=0, **kwargs)[source]

Selects top features based on importance weights using a Random Forest regressor.

name = 'RF Regressor Select From Model'
model_family = 'none'
hyperparameter_ranges = {'percent_features': Real(low=0.01, high=1, prior='uniform', transform='identity'), 'threshold': ['mean', -inf]}
default_parameters = {'max_depth': None, 'n_estimators': 10, 'n_jobs': -1, 'number_features': None, 'percent_features': 0.5, 'threshold': -inf}

Instance attributes

needs_fitting

parameters

Returns the parameters which were used to initialize the component

Methods:

__init__

Initialize self.

clone

Constructs a new component with the same parameters

describe

Describe a component and its parameters

fit

Fits component to data

fit_transform

Fits feature selector on data X then transforms X by selecting features

get_names

Get names of selected features.

load

Loads component at file path

save

Saves component at file path

transform

Transforms data X by selecting features

Class Inheritance

Inheritance diagram of RFRegressorSelectFromModel