August 2014
Beginner to intermediate
304 pages
7h 10m
English
Content preview from Python 3 Text Processing with NLTK 3 Cookbook - Second EditionBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Calculating high information words
A high information word is a word that is strongly biased towards a single classification label. These are the kinds of words we saw when we called the show_most_informative_features() method on both the NaiveBayesClassifier class and the MaxentClassifier class. Somewhat surprisingly, the top words are different for both classifiers. This discrepancy is due to how each classifier calculates the significance of each feature, and it's actually beneficial to have these different methods as they can be combined to improve accuracy, as we will see in the next recipe, Combining classifiers with voting.
The low information words are words that are common to all labels. It may be counter-intuitive, but eliminating these ...
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