O'Reilly logo

Python 3 Text Processing with NLTK 3 Cookbook by Jacob Perkins

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

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 ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required