input: 
  from sklearn.naive_bayes import MultinomialNB
  
  def classify_string(input_string):
      """
      Given an input string, this function extracts features from the string,
      trains a Multinomial Naive Bayes classifier on the data, and returns the
      prediction on the input string.
      >>> classify_string("Hello")
      ['greeting']
      >>> classify_string("How are you?")
      ['query']
      """
      # 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 = [len(input_string), input_string.count(' ')]
  
      # Sample data for training
      data = [[5, 1], [11, 2]]
      target = ['greeting', 'query']
  
      # 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