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Python Machine Learning By Example

You're reading from   Python Machine Learning By Example The easiest way to get into machine learning

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781783553112
Length 254 pages
Edition 1st Edition
Languages
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Authors (2):
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Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Toc

Table of Contents (9) Chapters Close

Preface 1. Getting Started with Python and Machine Learning FREE CHAPTER 2. Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms 3. Spam Email Detection with Naive Bayes 4. News Topic Classification with Support Vector Machine 5. Click-Through Prediction with Tree-Based Algorithms 6. Click-Through Prediction with Logistic Regression 7. Stock Price Prediction with Regression Algorithms 8. Best Practices

The naive Bayes implementations

After a hand-calculating spam email detection example, as promised, we are going to code it through a genuine dataset, taken from the Enron email dataset http://www.aueb.gr/users/ion/data/enron-spam/. The specific dataset we are using can be directly downloaded via http://www.aueb.gr/users/ion/data/enron-spam/preprocessed/enron1.tar.gz. You can either unzip it using a software or run the command line tar -xvz enron1.tar.gz in the Terminal. The uncompressed folder includes a folder of ham email text files and a folder of spam email text files, as well as a summary description of the database:

    enron1/
ham/
0001.1999-12-10.farmer.ham.txt
0002.1999-12-13.farmer.ham.txt
......
......
5172.2002-01-11.farmer.ham.txt
spam/
0006.2003-12-18.GP.spam.txt
0008.2003-12-18.GP.spam.txt
......
......
5171.2005-09-06.GP.spam.txt
Summary.txt

Given a dataset for...

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