input: Write a python function to classify a given article using a NaiveBayesClassifier and predefined training data.
  assert classify_article("President Trump is expected to unveil a new immigration plan on Wednesday.") == "Politics"
  assert classify_article("Apple's share in the market has seen a significant rise recently.") == "Business"
  assert classify_article("The singer gave an outstanding performance during the concert last night.") == "Entertainment"
  assert classify_article("The player scored the winning goal for his team in the final match.") == "Sports"
output: def classify_article(article):
      from textblob import TextBlob
      from textblob.classifiers import NaiveBayesClassifier
  
      training_data = [
          ('The government has announced new policies for economic growth.', 'Politics'),
          ('The stock market saw a significant increase in the value of tech stocks.', 'Business'),
          ('The movie received critical acclaim and won several awards.', 'Entertainment'),
          ('The athlete broke the world record in the 100 meters sprint.', 'Sports'),
          ('A debate on the new healthcare bill is scheduled for next week.', 'Politics'),
          ('A new smartphone model was released by a major tech company.', 'Business'),
          ('The band released their latest album to much fanfare.', 'Entertainment'),
          ('The team won the championship after a thrilling match.', 'Sports')
      ]
  
      classifier = NaiveBayesClassifier(training_data)
      return classifier.classify(article)