code: def test_ebm_unknown_value_at_predict():
      """Tests if unsigned integers can be handled when unknown values
      are found by predict.
  
      e.g. feature 3 has only 0's in X but a 1 in X_test.
      """
      X = np.array(
          [
              [0, 1, 0, 0],
              [0, 0, 0, 1],
              [0, 0, 0, 0],
              [1, 0, 0, 0],
              [0, 0, 0, 1],
          ],
          dtype=np.uint8,
      )
  
      X_test = np.array(
          [[0, 1, 0, 0], [0, 0, 1, 1], [1, 0, 0, 0]], dtype=np.uint8
      )
  
      y = np.array([0, 1, 1, 1, 1], dtype=np.uint8)
  
      clf = ExplainableBoostingClassifier()
      clf.fit(X, y)
      clf.predict(X_test)
  
      valid_ebm(clf)
  
imports: import math
  from sklearn.metrics import log_loss
  from interpret.utils import make_synthetic
  from ...tutils import synthetic_multiclass, synthetic_classification, iris_classification, smoke_test_explanations
  from ...tutils import synthetic_regression
  from interpret.glassbox import ExplainableBoostingRegressor, ExplainableBoostingClassifier
  from interpret.privacy import DPExplainableBoostingClassifier, DPExplainableBoostingRegressor
  from interpret.utils import inv_link
  from io import StringIO
  import json
  import numpy
  import pandas
  from sklearn.model_selection import train_test_split
  from sklearn.metrics import accuracy_score
  from sklearn.utils.estimator_checks import check_estimator
  import pytest
  import warnings
label_desc: Use image node_id 36 for calling a global function with example usage: test_ebm_unknown_value_at_predict() without return types