evalml.pipelines.components.ElasticNetClassifier

class evalml.pipelines.components.ElasticNetClassifier(alpha=0.0001, l1_ratio=0.15, n_jobs=- 1, max_iter=1000, random_seed=0, penalty='elasticnet', **kwargs)[source]

Elastic Net Classifier.

name = 'Elastic Net Classifier'
model_family = 'linear_model'
supported_problem_types = [<ProblemTypes.BINARY: 'binary'>, <ProblemTypes.MULTICLASS: 'multiclass'>, <ProblemTypes.TIME_SERIES_BINARY: 'time series binary'>, <ProblemTypes.TIME_SERIES_MULTICLASS: 'time series multiclass'>]
hyperparameter_ranges = {'alpha': Real(low=0, high=1, prior='uniform', transform='identity'), 'l1_ratio': Real(low=0, high=1, prior='uniform', transform='identity')}
default_parameters = {'alpha': 0.0001, 'l1_ratio': 0.15, 'loss': 'log', 'max_iter': 1000, 'n_jobs': -1, 'penalty': 'elasticnet'}
predict_uses_y = False

Instance attributes

feature_importance

Return an attribute of instance, which is of type owner.

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

load

Loads component at file path

predict

Make predictions using selected features.

predict_proba

Make probability estimates for labels.

save

Saves component at file path

Class Inheritance

Inheritance diagram of ElasticNetClassifier