Difference between revisions of "Class meeting for 10-605 in Fall 2016 Probability Review"
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* None | * None | ||
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| + | === Things to remember === | ||
| + | |||
| + | * The joint probability distribution | ||
| + | * Brute-force estimation of a joint distribution | ||
| + | * Density estimation and how it can be used for classification | ||
| + | * Naive Bayes and the conditional independence assumption | ||
| + | * Asymptotic complexity of naive Bayes | ||
Revision as of 13:23, 14 October 2015
This is one of the class meetings on the schedule for the course Machine Learning with Large Datasets 10-605 in Spring_2015.
Slides
Readings for the Class
- None
Things to remember
- The joint probability distribution
- Brute-force estimation of a joint distribution
- Density estimation and how it can be used for classification
- Naive Bayes and the conditional independence assumption
- Asymptotic complexity of naive Bayes
