input: def sentiment_analysis(tweets):
      """
      Classify tweets into positive or negative sentiment.
  
      >>> sentiment_analysis(["I love this product!", "This is terrible."])
      ['Positive', 'Negative']
      >>> sentiment_analysis(["Great job everyone!", "I can't stand this."])
      ['Positive', 'Negative']
      """
      results = []
      for tweet in tweets:
          tweet = preprocessing(tweet)
          tweet_vector = vectorize(tweet)
          prediction = predict_sentiment(tweet_vector)
          if prediction == 1:
              results.append("Positive")
          elif prediction == 0:
              results.append("Negative")
      return results
output:     results = []
      for tweet in tweets:
          tweet = preprocessing(tweet)
          tweet_vector = vectorize(tweet)
          prediction = predict_sentiment(tweet_vector)
          if prediction == 1:
              results.append("Positive")
          elif prediction == 0:
              results.append("Negative")
      return results