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 5. How to Address a Data Mining Problem – Data Cleaning and Validation

This chapter is where our real journey begins (finally!, I can hear you exclaiming). We are now familiar enough with R and the data mining process and architecture to get involved with a real problem.

I say real problem I actually mean real, since we are going to face something that actually happened and that actually puzzled a non-trivial number of people in a real company. Of course, we are going to use randomized dataF here and fictitious names, nevertheless, this will not remove any pathos to the problem. We are shortly going to get immersed into some kind of mystery that actually came up, and we will need to solve it, employing data mining techniques. 

I know you may be thinking: OK, don't make it too serious, is it something which actually already got solved?You would be right, but what if something similar pops up for you some day in the future? What would you do? The mystery we are going to face will not...