Machine Learning for Email
Autor Drew Conway, John Myles Whiteen Limba Engleză Paperback – 24 noi 2011
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
ISBN-10: 1449314309
Pagini: 146
Dimensiuni: 178 x 234 x 9 mm
Greutate: 0.25 kg
Editura: O'Reilly
Notă biografică
Cuprins
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."