evalml.pipelines.components.LogisticRegressionClassifier

class evalml.pipelines.components.LogisticRegressionClassifier(penalty='l2', C=1.0, n_jobs=-1, random_state=0)[source]

Logistic Regression Classifier

name = 'Logistic Regression Classifier'
model_family = 'linear_model'
supported_problem_types = [<ProblemTypes.BINARY: 'binary'>, <ProblemTypes.MULTICLASS: 'multiclass'>]
hyperparameter_ranges = {'C': Real(low=0.01, high=10, prior='uniform', transform='identity'), 'penalty': ['l2']}

Instance attributes

feature_importances

Returns feature importances.

Methods:

__init__

Initialize self.

describe

Describe a component and its parameters

fit

Fits component to data

predict

Make predictions using selected features.

predict_proba

Make probability estimates for labels.