How to use the ngboost.distns.Bernoulli function in ngboost

To help you get started, we’ve selected a few ngboost examples, based on popular ways it is used in public projects.

Secure your code as it's written. Use Snyk Code to scan source code in minutes - no build needed - and fix issues immediately.

github stanfordmlgroup / ngboost / tests / test_basic.py View on Github external
def test_classification(self):
        data, target = load_breast_cancer(True)
        x_train, x_test, y_train, y_test = train_test_split(data, target,
                                                            test_size=0.2,
                                                            random_state=42)
        ngb = NGBoost(Base=default_tree_learner, Dist=Bernoulli, Score=MLE,
                      verbose=False)
        ngb.fit(x_train, y_train)
        preds = ngb.pred_dist(x_test)
        score = roc_auc_score(y_test, preds.prob)
        assert score >= 0.95
github stanfordmlgroup / ngboost / ngboost / api.py View on Github external
def __init__(
        self,
        Dist=Bernoulli,
        Score=LogScore,
        Base=default_tree_learner,
        natural_gradient=True,
        n_estimators=500,
        learning_rate=0.01,
        minibatch_frac=1.0,
        col_sample=1.0,
        verbose=True,
        verbose_eval=100,
        tol=1e-4,
        random_state=None,
    ):
        assert issubclass(
            Dist, ClassificationDistn
        ), f"{Dist.__name__} is not useable for classification."
        super().__init__(
github stanfordmlgroup / ngboost / ngboost / sklearn_api.py View on Github external
def __init__(self, *args, **kwargs):
        super(NGBClassifier, self).__init__(Dist=Bernoulli, *args, **kwargs)