input: 
  from sklearn.naive_bayes import GaussianNB
  
  def classify_emails(X_train, y_train, X_test):
      """ Construct a naive bayes classifier using python to classify emails as spam or not spam.
      >>> X_train = [[0, 1], [1, 0], [1, 1], [0, 0]]
      >>> y_train = [0, 1, 1, 0]
      >>> X_test = [[1, 0], [0, 1]]
      >>> classify_emails(X_train, y_train, X_test)
      [1, 0]
      """
      # 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