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About MachineLearning Lecture06 PDF
The instructor provides an overview of Naive Bayes classifiers and discusses two variations: 1) Allowing features to take on multiple values rather than just binary 0/1, such as discretizing continuous variables. 2) Using a multinomial event model to represent text by counting word frequencies rather than binary presence, with features indicating the words in each position. 3) The parameters of the multinomial model are the probabilities of each word given the class, estimated from maximum likelihood on the training data.
Detailed Information
| Author: | ['Sethu S'] |
|---|---|
| Publication Year: | 2013 |
| Pages: | 16 |
| Language: | English |
| Format: | |
| Price: | FREE |
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