input: 
  from sklearn.naive_bayes import GaussianNB
  
  def classify_emails_as_spam(X_train, y_train, X_test):
      """Construct a naive Bayes classifier to classify emails as spam or not spam.
      The classifier is trained on the given training data and predicts the output
      for the test data.
      >>> X_train = [[1, 2], [2, 3], [3, 4]]
      >>> y_train = [0, 1, 0]
      >>> X_test = [[4, 5], [5, 6]]
      >>> classify_emails_as_spam(X_train, y_train, X_test)
      [0, 1]
      """
      # Create a Gaussian Classifier
      model = GaussianNB()
      
      # Train the model using the training sets 
      model.fit(X_train, y_train)
      
      # Predict Output 
      y_pred = model.predict(X_test)
      return y_pred
  
output:     # Create a Gaussian Classifier
      model = GaussianNB()
      
      # Train the model using the training sets 
      model.fit(X_train, y_train)
      
      # Predict Output 
      y_pred = model.predict(X_test)
      return y_pred