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I'm currently working on a school project to classify abstracts from papers in to 4 categories. Currently Bernoulli Naive Bayes scores 85% accuracy. For compari

• rasbt 12y ago
  Sounds cool. I think the most crucial part is really the data (or feature) set. The choice of classifiers makes a difference too, but having good data (salient, invariant, discriminatory) makes the largest difference. One think about naive Bayes and kNN: Although the performance may be similar, I would consider Naive beneficial if the data set is large. kNN requires to re-evaluate the data. Naive Bayes makes the classification computationally cheaper and with "on-line" learning, you can still improve or adjust it over time