Current Slide
Small screen detected. You are viewing the mobile version of SlideWiki. If you wish to edit slides you will need to use a larger device.
Two Models
Model 2: Multinomial = Class conditional unigram
One feature Xi for each word pos in document
feature’s values are all words in dictionary
Value of Xi is the word in position i
Naïve Bayes assumption:
Given the document’s topic, word in one position in the document tells us nothing about words in other positions
Second assumption:
Word appearance does not depend on position
P(Xi = w | c) = P(Xj = w | c)
Just have one multinomial feature predicting all words
for all positions i,j, word w, and class c
Speaker notes:
Content Tools
Tools
Sources (0)
Tags (0)
Comments (0)
History
Usage
Questions (0)
Playlists (0)
Quality
Sources
There are currently no sources for this slide.