Book Image

R Data Mining

Book Image

R Data Mining

Overview of this book

R is widely used to leverage data mining techniques across many different industries, including finance, medicine, scientific research, and more. This book will empower you to produce and present impressive analyses from data, by selecting and implementing the appropriate data mining techniques in R. It will let you gain these powerful skills while immersing in a one of a kind data mining crime case, where you will be requested to help resolving a real fraud case affecting a commercial company, by the mean of both basic and advanced data mining techniques. While moving along the plot of the story you will effectively learn and practice on real data the various R packages commonly employed for this kind of tasks. You will also get the chance of apply some of the most popular and effective data mining models and algos, from the basic multiple linear regression to the most advanced Support Vector Machines. Unlike other data mining learning instruments, this book will effectively expose you the theory behind these models, their relevant assumptions and when they can be applied to the data you are facing. By the end of the book you will hold a new and powerful toolbox of instruments, exactly knowing when and how to employ each of them to solve your data mining problems and get the most out of your data. Finally, to let you maximize the exposure to the concepts described and the learning process, the book comes packed with a reproducible bundle of commented R scripts and a practical set of data mining models cheat sheets.
Table of Contents (22 chapters)
Title Page
Credits
About the Author
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
14
Epilogue

Chapter 7. Our First Guess – a Linear Regression

Still smiling from the successful EDA you just obtained, you follow Andy, the colleague who helped you with it, and walk into the office of your boss, Mr. Sheen: Have you finally discovered where all this mess is coming from? Not exactly what you would call a warm welcome, I agree.

Nevertheless, your colleague seems to be quite used to these kinds of high-pressure situations and quietly starts to expose all the analyses you have performed, from the summary statistics to the graphical EDA. Your boss is some kind of hybrid profile and Andy knows that: exposing your work with a sufficient level of detail will help your boss understand that, despite the great hurry the work was done in, it was done in the most accurate way possible. 

Andy finally comes to the point—the cash flow recorded within the last quarter is coming from the Middle East area.

"The Middle East? We have not been there for a long time. Nevertheless, I personally know Marc, the...