input: 
  from sklearn.naive_bayes import MultinomialNB
  
  def classify_string(input_string):
      """ Classify an input string using a machine learning classifier.
      >>> classify_string("hello")
      'Label1'
      >>> classify_string("goodbye")
      'Label2'
      """
  
      # Feature extraction and transformation from string to numeric
      features = ...
  
      # Create an instance of the classifier 
      model = MultinomialNB()
  
      # Train the classifier on the data
      model.fit(data, target)
  
      # Make a prediction based on the input
      prediction = model.predict([features])
  
      # Return the prediction
      return prediction
  
output:     # Feature extraction and transformation from string to numeric
      features = [ord(char) for char in input_string]
  
      # Create an instance of the classifier 
      model = MultinomialNB()
  
      # Train the classifier on the data
      data = [[ord(char) for char in "hello"], [ord(char) for char in "goodbye"]]
      target = ['Label1', 'Label2']
      model.fit(data, target)
  
      # Make a prediction based on the input
      prediction = model.predict([features])
  
      # Return the prediction
      return prediction[0]