evalml.pipelines.components.LogisticRegressionClassifier¶
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class
evalml.pipelines.components.
LogisticRegressionClassifier
(penalty='l2', C=1.0, n_jobs=- 1, multi_class='auto', solver='lbfgs', random_seed=0, **kwargs)[source]¶ Logistic Regression Classifier.
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name
= 'Logistic Regression Classifier'¶
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model_family
= 'linear_model'¶
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supported_problem_types
= [<ProblemTypes.BINARY: 'binary'>, <ProblemTypes.MULTICLASS: 'multiclass'>, <ProblemTypes.TIME_SERIES_BINARY: 'time series binary'>, <ProblemTypes.TIME_SERIES_MULTICLASS: 'time series multiclass'>]¶
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hyperparameter_ranges
= {'C': Real(low=0.01, high=10, prior='uniform', transform='identity'), 'penalty': ['l2']}¶
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default_parameters
= {'C': 1.0, 'multi_class': 'auto', 'n_jobs': -1, 'penalty': 'l2', 'solver': 'lbfgs'}¶
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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:
Initialize self.
Constructs a new component with the same parameters and random state.
Describe a component and its parameters
Fits component to data
Loads component at file path
Make predictions using selected features.
Make probability estimates for labels.
Saves component at file path
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