def test_proba2d(self):
proba1d = np.array([1, 0.5, 0, 0])
proba2d = np.array([[0, 1], [0.5, 0.5], [1, 0], [1, 0]])
np.testing.assert_equal(utmdl.proba2d(proba1d=proba1d), proba2d)
def predict_proba(self, X) -> np.ndarray:
dsn_pred = self.decision_function(X)
dsn_pred = 1 / (1 + np.exp(-dsn_pred))
return utmdl.proba2d(proba1d=dsn_pred)
def predict_proba(self, X):
proba = gam.LogisticGAM.predict_proba(self, X)
return utmdl.proba2d(proba1d=proba)
def predict_proba(self, X) -> np.ndarray:
skutilvalid.check_is_fitted(self, ['model_'])
dsn_pred = self.decision_function(X)
return utmdl.proba2d(proba1d=dsn_pred)