input: Write a function to classify positive and negative sentiment in tweets. If the sentiment prediction is 1, it should append "Positive" to the result list; if the sentiment prediction is 0, it should append "Negative".
  
  def sentiment_analysis(tweets):
      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
  
  assert sentiment_analysis(["I love this product!", "This is terrible"])==["Positive", "Negative"]
  assert sentiment_analysis(["I hate Mondays", "Super excited for the weekend"])==["Negative", "Positive"]
  assert sentiment_analysis([])==[]
output: def sentiment_analysis(tweets):
      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