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API: modeling.classification

skyulf.modeling.classification

Classification models.

LogisticRegressionApplier

Bases: SklearnApplier

Logistic Regression Applier.

Source code in skyulf-core\skyulf\modeling\classification.py 
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class LogisticRegressionApplier(SklearnApplier):
    """Logistic Regression Applier."""

    pass

LogisticRegressionCalculator

Bases: SklearnCalculator

Logistic Regression Calculator.

Source code in skyulf-core\skyulf\modeling\classification.py 
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@NodeRegistry.register("logistic_regression", LogisticRegressionApplier)
class LogisticRegressionCalculator(SklearnCalculator):
    """Logistic Regression Calculator."""

    def __init__(self):
        super().__init__(
            model_class=LogisticRegression,
            default_params={
                "max_iter": 1000,
                "solver": "lbfgs",
                "random_state": 42,
            },
            problem_type="classification",
        )

RandomForestClassifierApplier

Bases: SklearnApplier

Random Forest Classifier Applier.

Source code in skyulf-core\skyulf\modeling\classification.py 
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class RandomForestClassifierApplier(SklearnApplier):
    """Random Forest Classifier Applier."""

    pass

RandomForestClassifierCalculator

Bases: SklearnCalculator

Random Forest Classifier Calculator.

Source code in skyulf-core\skyulf\modeling\classification.py 
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@NodeRegistry.register("random_forest_classifier", RandomForestClassifierApplier)
class RandomForestClassifierCalculator(SklearnCalculator):
    """Random Forest Classifier Calculator."""

    def __init__(self):
        super().__init__(
            model_class=RandomForestClassifier,
            default_params={
                "n_estimators": 50,
                "max_depth": 10,
                "min_samples_split": 5,
                "min_samples_leaf": 2,
                "n_jobs": -1,
                "random_state": 42,
            },
            problem_type="classification",
        )