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Book Overview & Buying
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Table Of Contents
Machine Learning For Dummies
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The previous NLP discussions in this chapter show how a machine learning algorithm can read text (after scraping it from the web) using the BoW representation and how NLP can enhance its understanding of text using text length normalization, TF-IDF model, and n-grams. The following sections demonstrate how to put text processing into use by learning to solve two common problems in textual analysis: classification and sentiment analysis.
Performing classification tasks
When you classify texts, you assign a document to a class because of the topics it discusses. You can discover the topics in a document in different ways. The simplest approach is prompted by the idea that if a group of people talks or writes about a topic, the people tend to use words from a limited vocabulary because they refer or relate to the same topic. When you share some meaning or are part of the same group, you tend to use the same language. Consequently, if you have a collection...
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