input: Write a function to evaluate the accuracy of a machine-learning model. The function should take a trained classifier and the test data as input, and return the accuracy of the model on the test data. If the test data is empty, the function should return 0. 
  
  assert evaluate_accuracy(clf, X_test, y_test)==0.85
  assert evaluate_accuracy(clf, [], y_test)==0
  assert evaluate_accuracy(clf, X_test, [])==0
  assert evaluate_accuracy(clf, [], [])==0
output: def evaluate_accuracy(classifier, X_test, y_test):
      if not X_test or not y_test:
          return 0
      return classifier.score(X_test, y_test)