input: Write a function to classify a given input string using a machine learning classifier. The function should use a Multinomial Naive Bayes classifier, perform feature extraction and transformation from the string to numeric values, train the classifier on the data, and return the prediction.
  
  def classify_string(input_string):
    features = . . .
    model = MultinomialNB()
    model.fit(data, target)
    prediction = model.predict([features])
    return prediction
  
  assert classify_string("Hello") == [1]
  assert classify_string("Goodbye") == [0]
  assert classify_string("How are you?") == [1]
  assert classify_string("") == [0]
  assert classify_string("Hi") == [1]
output: def classify_string(input_string):
    from sklearn.feature_extraction.text import CountVectorizer
    from sklearn.naive_bayes import MultinomialNB
    data = ["Hello", "Goodbye", "How are you?", "", "Hi"]
    target = [1, 0, 1, 0, 1]
    vectorizer = CountVectorizer()
    X = vectorizer.fit_transform(data)
    model = MultinomialNB()
    model.fit(X, target)
    features = vectorizer.transform([input_string])
    prediction = model.predict(features)
    return prediction