Difference between revisions of "Class meeting for 10-405 Streaming Naive Bayes"

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(Quiz)
(Things to Remember)
 
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=== Things to Remember ===
 
=== Things to Remember ===
 +
 +
* What TFIDF weighting is and how to compute it
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** Computing DFs requires extra pass over training set
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* How it's used in Rocchio
  
 
* Zipf's law and the prevalence of rare features/words
 
* Zipf's law and the prevalence of rare features/words
 +
 
* Communication complexity
 
* Communication complexity
 
* Stream and sort
 
* Stream and sort

Latest revision as of 10:07, 5 March 2018

This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-405 in Spring 2018.

Contents

Slides

Quiz

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

  • What TFIDF weighting is and how to compute it
    • Computing DFs requires extra pass over training set
  • How it's used in Rocchio
  • 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