input: 
  from sklearn.naive_bayes import MultinomialNB 
  
  def classify_string(input_string):
      """Given a user input string, extract features from the string and classify it using a Multinomial Naive Bayes classifier.
      The input string should be transformed into a numeric form suitable for the classifier.
      The classifier is trained on a dataset, and the prediction for the input string is returned.
      Example:
      >>> classify_string("Hello world")
      [0]  # Assuming the model was trained to classify into two categories and "Hello world" falls into category 0.
      """
      # 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 "World"]]
      target = [0, 1]
      model.fit(data, target)
  
      # Make a prediction based on the input
      prediction = model.predict([features])
  
      # Return the prediction
      return prediction