code: def test_json_dp_classification():
      data = synthetic_classification()
      X = data["full"]["X"]
      y = data["full"]["y"]
      feature_types = ["continuous"] * X.shape[1]
      feature_types[0] = "nominal"
  
      with warnings.catch_warnings():
          warnings.filterwarnings(
              "ignore", "Possible privacy violation*"
          )
          warnings.filterwarnings(
              "ignore", "JSON formats are in beta.*"
          )
  
          clf = DPExplainableBoostingClassifier(
              max_bins=10, feature_types=feature_types
          )
          clf.fit(X, y)
          clf.term_scores_[0][0] = np.nan
          clf.term_scores_[0][1] = np.inf
          clf.term_scores_[0][2] = -np.inf
          clf.to_jsonable(detail="all")
  
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 42 for calling a global function with example usage: test_json_dp_classification() without return types