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

Business understanding


This is an often underestimated phase, and we should look at it carefully since its role is decisive for all of the remaining phases. Within the business understanding phase, we fundamentally answer the following two questions:

  • What are the objectives of the business where the data mining problem is coming from?
  • What are the data mining goals for this project?

Giving the wrong answer to either one of these two questions will result in producing results not relevant for the business, or not solving the data mining problem at its core.

The first step in this phase is understanding your client's needs and objectives, since those objectives will become the objectives of the project. Within this phase, we gather information through the means of interviews and technical literature, finally defining a project plan and clearly stating a data mining goal and how we plan to reach it.

The project plan should not be considered an unchangeable one, since the following phases will naturally...