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)

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]}

Instance attributes

Methods:

__init__	Initialize self.
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_indices	Get integer index of features selected
get_names	Get names of selected features.
transform	Transforms data X by selecting features