This chapter presents recipes to build text classifiers. This includes extracting vital features from the database, training, testing, and validating the text classifier. Initially, a text classifier is trained using commonly used words. Later, the trained text classifier is used for prediction. Building a text classifier includes preprocessing the data using tokenization, stemming text data, dividing text using chunking, and building a bag-of-words model.
Germany
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Norway
Chile
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Finland
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Romania
Greece
Argentina
Malaysia
South Africa
Netherlands
Bulgaria
Latvia
Australia
Japan
Russia