Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python 3 Text Processing with NLTK 3 Cookbook

You're reading from   Python 3 Text Processing with NLTK 3 Cookbook

Arrow left icon
Product type Paperback
Published in Aug 2014
Publisher
ISBN-13 9781782167853
Length 304 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Jacob Perkins Jacob Perkins
Author Profile Icon Jacob Perkins
Jacob Perkins
Arrow right icon
View More author details
Toc

Table of Contents (12) Chapters Close

Preface 1. Tokenizing Text and WordNet Basics FREE CHAPTER 2. Replacing and Correcting Words 3. Creating Custom Corpora 4. Part-of-speech Tagging 5. Extracting Chunks 6. Transforming Chunks and Trees 7. Text Classification 8. Distributed Processing and Handling Large Datasets 9. Parsing Specific Data Types A. Penn Treebank Part-of-speech Tags
Index

Training scikit-learn classifiers


Scikit-learn is one of the best machine learning libraries available in any programming language. It contains all sorts of machine learning algorithms for many different purposes, but they all follow the same fit/predict design pattern:

  • Fit the model to the data

  • Use the model to make predictions

We won't be accessing the scikit-learn models directly in this recipe. Instead, we'll be using NLTK's SklearnClassifier class, which is a wrapper class around a scikit-learn model to make it conform to NLTK's ClassifierI interface. This means that the SklearnClassifier class can be trained and used much like the classifiers we've used in the previous recipes in this chapter.

Note

I may use the terms scikit-learn and sklearn interchangeably in this recipe.

Getting ready

To use the SklearnClassifier class, you must have scikit-learn installed. Instructions are available online at http://scikit-learn.org/stable/install.html. If you have all the dependencies installed, such...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime