[math] What is "entropy and information gain"?

As you are reading a book about NLTK it would be interesting you read about MaxEnt Classifier Module http://www.nltk.org/api/nltk.classify.html#module-nltk.classify.maxent

For text mining classification the steps could be: pre-processing (tokenization, steaming, feature selection with Information Gain ...), transformation to numeric (frequency or TF-IDF) (I think that this is the key step to understand when using text as input to a algorithm that only accept numeric) and then classify with MaxEnt, sure this is just an example.

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