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Mastering Machine Learning with R, Second Edition

You're reading from   Mastering Machine Learning with R, Second Edition Advanced prediction, algorithms, and learning methods with R 3.x

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Product type Paperback
Published in Apr 2017
Publisher Packt
ISBN-13 9781787287471
Length 420 pages
Edition 2nd Edition
Languages
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Author (1):
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Cory Lesmeister Cory Lesmeister
Author Profile Icon Cory Lesmeister
Cory Lesmeister
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Toc

Table of Contents (17) Chapters Close

Preface 1. A Process for Success FREE CHAPTER 2. Linear Regression - The Blocking and Tackling of Machine Learning 3. Logistic Regression and Discriminant Analysis 4. Advanced Feature Selection in Linear Models 5. More Classification Techniques - K-Nearest Neighbors and Support Vector Machines 6. Classification and Regression Trees 7. Neural Networks and Deep Learning 8. Cluster Analysis 9. Principal Components Analysis 10. Market Basket Analysis, Recommendation Engines, and Sequential Analysis 11. Creating Ensembles and Multiclass Classification 12. Time Series and Causality 13. Text Mining 14. R on the Cloud 15. R Fundamentals 16. Sources

Business understanding

For this case study, we will take a look at president Obama's State of the Union speeches. I have no agenda here; just curious as to what can be uncovered in particular and if and how his message changed over time. Perhaps this will serve as a blueprint to analyze any politician's speech in order to prepare an opposing candidate in a debate or speech of their own. If not, so be it.

The two main analytical goals are to build topic models on the six State of the Union speeches and then compare the first speech in 2010 and the last in January, 2016 for sentence-based textual measures, such as sentiment and dispersion.

Data understanding and preparation

The primary package that we will use is tm, the text mining package. We will also...

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