Difference between revisions of "Class meeting for 10-605 Streaming Naive Bayes"

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* [http://www.cs.cmu.edu/~wcohen/10-605/stream-and-sort.pptx Slides in Powerpoint] - the stream-and-sort pattern, and large-vocabulary Naive Bayes
 
* [http://www.cs.cmu.edu/~wcohen/10-605/stream-and-sort.pptx Slides in Powerpoint] - the stream-and-sort pattern, and large-vocabulary Naive Bayes
 
* [http://www.cs.cmu.edu/~wcohen/10-605/stream-and-sort.pdf Slides in PDF]  
 
* [http://www.cs.cmu.edu/~wcohen/10-605/stream-and-sort.pdf Slides in PDF]  
* [https://qna.cs.cmu.edu/#/pages/view/161]
+
* [https://qna.cs.cmu.edu/#/pages/view/161 Today's quiz]
  
 
=== Readings for the Class ===
 
=== Readings for the Class ===

Revision as of 12:03, 5 September 2017

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

Slides

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