Class meeting for 10-605 Streaming Naive Bayes
From Cohen Courses
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