input: Write a function to identify the author of a given article using a machine learning model in Python. The function should use a TF-IDF vectorizer and a Gaussian Naive Bayes classifier. If the article is correctly identified as belonging to an author, return the author's name. If the article is not correctly identified, return "Unknown". If the input article is empty, return "No input provided".
  assert identify_author(["sample 1 from AuthorA", "sample 2 from AuthorA", "sample 1 from AuthorB", "sample 2 from AuthorB"], ["AuthorA", "AuthorA", "AuthorB", "AuthorB"], "sample 1 from AuthorA")=="AuthorA"
  assert identify_author(["sample 1 from AuthorA", "sample 2 from AuthorA", "sample 1 from AuthorB", "sample 2 from AuthorB"], ["AuthorA", "AuthorA", "AuthorB", "AuthorB"], "sample 3 from AuthorC")=="Unknown"
  assert identify_author(["sample 1 from AuthorA", "sample 2 from AuthorA", "sample 1 from AuthorB", "sample 2 from AuthorB"], ["AuthorA", "AuthorA", "AuthorB", "AuthorB"], "")=="No input provided"
  assert identify_author([], [], "sample 1 from AuthorA")=="No input provided"
output: def identify_author(articles, authors, article):
      if not article:
          return "No input provided"
      if not articles or not authors:
          return "No input provided"
      
      from sklearn.feature_extraction.text import TfidfVectorizer
      from sklearn.naive_bayes import GaussianNB
      from sklearn.model_selection import train_test_split
      from sklearn.preprocessing import LabelEncoder
      import numpy as np
  
      vectorizer = TfidfVectorizer()
      X = vectorizer.fit_transform(articles).toarray()
      y = LabelEncoder().fit_transform(authors)
  
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
  
      model = GaussianNB()
      model.fit(X_train, y_train)
  
      article_vec = vectorizer.transform([article]).toarray()
      prediction = model.predict(article_vec)
  
      if prediction in y:
          return LabelEncoder().inverse_transform([prediction])[0]
      else:
          return "Unknown"