input: def sentiment_analysis(tweets):
      """ Classifies a list of tweets into positive or negative sentiment.
      >>> sentiment_analysis(["I love this!", "This is terrible."])
      ['Positive', 'Negative']
      >>> sentiment_analysis(["Amazing day!", "I hate Mondays."])
      ['Positive', 'Negative']
      """
      from typing import List
      results: List[str] = [] 
  
      for tweet in tweets:
          tweet = preprocessing(tweet)
          tweet_vector = vectorize(tweet)
          prediction = predict_sentiment(tweet_vector)
  
          if prediction == 1:
              results.append("Positive")
          else:
              results.append("Negative")
  
      return results
output:     from typing import List
      results: List[str] = [] 
  
      for tweet in tweets:
          tweet = preprocessing(tweet)
          tweet_vector = vectorize(tweet)
          prediction = predict_sentiment(tweet_vector)
  
          if prediction == 1:
              results.append("Positive")
          else:
              results.append("Negative")
  
      return results