Class meeting for 10-605 Streaming Naive Bayes

From Cohen Courses
Jump to: navigation, search

This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Fall 2017.




Readings for the Class

  • Required: my notes on streaming and Naive Bayes
  • Optional: If you're interested in reading more about smoothing for naive Bayes, I recommend this paper: Peng, Fuchun, Dale Schuurmans, and Shaojun Wang. "Augmenting naive Bayes classifiers with statistical language models." Information Retrieval 7.3 (2004): 317-345.

Things to Remember

  • Zipf's law and the prevalence of rare features/words
  • Communication complexity
  • Stream and sort
    • Complexity of merge sort
    • How pipes implement parallel processing
    • How buffering output before a sort can improve performance
    • How stream-and-sort can implement event-counting for naive Bayes