evalml.pipelines.components.RFClassifierSelectFromModel

class evalml.pipelines.components.RFClassifierSelectFromModel(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 classifier.

name = 'RF Classifier 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 and random state.

describe

Describe a component and its parameters

fit

Fits component to data

fit_transform

Fits on X and transforms X

get_names

Get names of selected features.

load

Loads component at file path

save

Saves component at file path

transform

Transforms input data by selecting features.

Class Inheritance

Inheritance diagram of RFClassifierSelectFromModel