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Machine Learning for Email
Publisher: O'Reilly Media, Inc.
Pub. Date: October 27, 2011
Print ISBN-13: 978-1-4493-1430-9
Pages in Print Edition: 148
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Overview
This compact book explores standard tools for text classification, and teaches the reader how to use machine learning to decide whether a e-mail is spam or ham (binary classification), based on raw data from The SpamAssassin Public Corpus. Of course, sometimes the items in one class are not created equally, or we want to distinguish among them in some meaningful way. The second part of the book will look at how to not only filter spam from our email, but also placing "more important" messages at the top of the queue. This is a curated excerpt from the upcoming book "Machine Learning for Hackers."
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