input: 
  from sklearn.naive_bayes import GaussianNB
  
  def train_and_predict_email_classifier(X_train, y_train, X_test):
      """
      Construct a Naive Bayes classifier to classify emails as spam or not spam.
      
      >>> X_train = [[1], [2], [3], [4], [5]]
      >>> y_train = [0, 0, 1, 1, 0]
      >>> X_test = [[6], [7]]
      >>> train_and_predict_email_classifier(X_train, y_train, X_test)
      [1, 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