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 4. Keeping the House Clean – The Data Mining Architecture

In the previous chapter, we defined the dynamic part of our data mining activities, understanding how a data mining project should be organized in terms of phases, input, and output. In this chapter, we are going to set our scene, defining the static part of our data mining projects, the data mining architecture.

How do we organize data bases, scripts, and output within our project? This is the question this chapter is going to answer. We are going to look at:

  • The general structure of data mining architecture
  • How to build such kind of structure with R

This is a really useful chapter, especially if you are approaching the data mining activity for the first time, and no matter the programming language, since it will let you gain a first view on what you will typically find in a data mining environment. No matter whether you are dealing with a single-man project or a whole team initiative, you will more or less always find the elements...