input: 
  from sklearn.naive_bayes import GaussianNB
  
  def spam_classifier():
      """Construct a naive bayes classifier using Python to classify emails as spam or not spam.
      >>> import numpy as np
      >>> X_train = np.array([[1, 2], [2, 3], [3, 4]])
      >>> y_train = np.array(['spam', 'not spam', 'spam'])
      >>> X_test = np.array([[1, 1], [4, 4]])
      >>> model = spam_classifier()
      >>> y_pred = model.predict(X_test)
      >>> y_pred
      array(['not spam', 'spam'], dtype='<U8')
      """
      # Create a Gaussian Classifier
      model = GaussianNB()
      
      return model
  
output:     # Fit the model with training data
      model.fit(X_train, y_train)