function naive_bayes_predict(features, class_priors, feature_likelihoods):

   best_class, best_score = None, -infinity
   for c in class_priors:
      score = log(class_priors[c])
      for feature in features:
        score += log(feature_likelihoods[c][feature]) # assumes features ar
 e independent
      if score > best_score:
        best_class, best_score = c, score

   return best_class
