input: def classify_emails(X_train, y_train, X_test):
      """Constructs a naive bayes classifier using python to classify emails as spam or not spam.
      The classifier is implemented using scikit-learn's Gaussian Naive Bayes model.
      >>> classify_emails([[1, 2], [2, 3]], [0, 1], [[1, 1], [2, 2]])
      array([0, 1])
      >>> classify_emails([[0, 0], [1, 1]], [1, 0], [[0, 0], [1, 1]])
      array([1, 0])
      """
      from sklearn.naive_bayes import GaussianNB
  
      # Create a Gaussian Classifier
      model = GaussianNB()
  
      # Train the model using the training sets 
      model.fit(X_train, y_train)
  
      # Predict Output 
      return model.predict(X_test)
output:     from sklearn.naive_bayes import GaussianNB
  
      # Create a Gaussian Classifier
      model = GaussianNB()
  
      # Train the model using the training sets 
      model.fit(X_train, y_train)
  
      # Predict Output 
      return model.predict(X_test)