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)[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]}

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