add test for uncertainty prediction function

Signed-off-by: Fabian Degen <fabian.degen@mytum.de>

python/interpret-core/tests/glassbox/ebm/test_ebm.py

@@ -1167,3 +1167,40 @@ def test_ebm_scale():
     assert len(clf.bagged_intercept_) == len(clf.bagged_scores_[0])
     assert len(clf.standard_deviations_) == 2
     assert len(clf.bin_weights_) == 2
+
+
+def test_ebm_uncertainty():
+    data = synthetic_classification()
+    X = data["full"]["X"]
+    y = data["full"]["y"]
+
+    clf = ExplainableBoostingClassifier(
+        outer_bags=5,
+        random_state=42,
+    )
+    clf.fit(X, y)
+
+    result = clf.pred_from_base_models_with_uncertainty(X)
+    assert result.shape == (len(X), 2), "Should return (n_samples, 2) shape"
+
+    clf2 = ExplainableBoostingClassifier(outer_bags=5, random_state=42)
+    clf2.fit(X, y)
+    result_same_seed = clf2.pred_from_base_models_with_uncertainty(X)
+    assert np.array_equal(
+        result,
+        result_same_seed,
+    ), "Results should be deterministic with same random seed"
+
+    X_far = X.copy()
+    X_far["A"] = X_far["A"] + 10.0  # Shift first feature far from training data
+    preds_far = clf.pred_from_base_models_with_uncertainty(X_far)
+
+    assert np.mean(preds_far[:, 1]) > np.mean(
+        result[:, 1]
+    ), "Uncertainty should be higher for points far from training data"
+
+    uncertainties = result[:, 1]
+    assert np.all(uncertainties >= 0), "Uncertainties should be non-negative"
+    assert not np.all(
+        uncertainties == uncertainties[0]
+    ), "Different samples should have different uncertainties"