input: 
  from typing import List, Tuple
  from sklearn.naive_bayes import GaussianNB
  
  def naive_bayes_classifier(X_train: List[Tuple[float]], y_train: List[int], X_test: List[Tuple[float]]) -> List[int]:
      """ Constructs a Naive Bayes classifier using the GaussianNB model from scikit-learn 
      to classify emails as spam (1) or not spam (0).
      >>> X_train = [(0.0, 1.0), (1.0, 2.0), (2.0, 3.0)]
      >>> y_train = [0, 1, 0]
      >>> X_test = [(3.0, 4.0), (4.0, 5.0)]
      >>> naive_bayes_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 
      return model.predict(X_test)
  
output:     # 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)