input: Write a function to classify user input using a machine learning classifier in Python. The function should use the Multinomial Naive Bayes algorithm for categorizing the input string. If the input string is empty, return an empty list.
  assert classify_string("I love programming")==[1]
  assert classify_string("I hate bugs")==[0]
  assert classify_string("")==[]
  assert classify_string("I enjoy learning new things")==[1]
  assert classify_string("I dislike repetitive tasks")==[0]
output: def classify_string(input_string):
      if not input_string:
          return []
      from sklearn.feature_extraction.text import CountVectorizer
      from sklearn.naive_bayes import MultinomialNB
      import numpy as np
      
      data = ["I love programming", "I hate bugs", "I enjoy learning new things", "I dislike repetitive tasks"]
      labels = [1, 0, 1, 0]
      
      vectorizer = CountVectorizer()
      X = vectorizer.fit_transform(data)
      
      clf = MultinomialNB()
      clf.fit(X, labels)
      
      input_vector = vectorizer.transform([input_string])
      prediction = clf.predict(input_vector)
      
      return prediction.tolist()