Book Image

Mastering Machine Learning with R, Second Edition - Second Edition

Book Image

Mastering Machine Learning with R, Second Edition - Second Edition

Overview of this book

This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more. You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you’ll understand how these concepts work and what they do. With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.
Table of Contents (23 chapters)
Title Page
Credits
About the Author
About the Reviewers
Packt Upsell
Customer Feedback
Preface
16
Sources

Chapter 13. Text Mining

"I think it's much more interesting to live not knowing than to have answers which might be wrong."                                                                                                                  - Richard Feynman

The world is awash with textual data. If you Google, Bing, or Yahoo how much of that data is unstructured, that is, in a textual format, estimates would range from 80 to 90 percent. The real number doesn't matter. What does matter is that a large proportion of the data is in a text format. The implication is that anyone seeking to find insights in that data must develop the capability to process and analyze text.

When I first started out as a market researcher, I used to manually pore through page after page of moderator-led focus groups and interviews with the hope of capturing some qualitative insight an Aha! moment if you will-and then haggle with fellow team members over whether they had the same insight or not. Then, you would always...