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

Principles of a good data mining report


I have written quite a lot of reports, highlighting results from a wide range of activities. Based on the feedback received and from the requests of changes intervened from the first version to the definitive one, I can tell you the following basic principles for producing a good data mining report:

  • Clearly show the objectives and questions that initiated the analyses performed
  • Explicitly highlight the assumptions made when performing the analyses
  • Enumerate and get into the details with data treatment applied to analyzed data
  • Always verify that the reproduced data is consistent
  • Provide data lineage to the maximum possible extent

Let's get a bit deeper into these principles before we actually develop our report.

Clearly state the objectives

When I was a newbie in the field, I got really excited at the idea of applying all the data mining techniques I knew by then to real data. You can imagine my happiness when I was first provided with a bunch of data. I was...