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Machine Learning for Email

Autor Drew Conway, John Myles White
en Limba Engleză Paperback – 24 noi 2011
If you’re an experienced programmer willing to crunch data, this concise guide will show you how to use machine learning to work with email. You’ll learn how to write algorithms that automatically sort and redirect email based on statistical patterns. Authors Drew Conway and John Myles White approach the process in a practical fashion, using a case-study driven approach rather than a traditional math-heavy presentation.

This book also includes a short tutorial on using the popular R language to manipulate and analyze data. You’ll get clear examples for analyzing sample data and writing machine learning programs with R.
* Mine email content with R functions, using a collection of sample files
* Analyze the data and use the results to write a Bayesian spam classifier
* Rank email by importance, using factors such as thread activity
* Use your email ranking analysis to write a priority inbox program
* Test your classifier and priority inbox with a separate email sample set
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Specificații

ISBN-13: 9781449314309
ISBN-10: 1449314309
Pagini: 146
Dimensiuni: 178 x 234 x 9 mm
Greutate: 0.25 kg
Editura: O'Reilly

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Descriere

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."