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
About the Author
About the Reviewers
Customer Feedback

Rendering and sharing an R markdown report 

You now have a sense of how flexible and useful this instrument can be in letting you organize and disclose the results from your data mining activity. 

Rendering an R markdown report

We are ready to deploy our report and take a look at it. We can easily do this by following two alternative ways:

  • Clicking on Run Document within the RStudio user interface:
  • Rendering the document through the render() function, which comes directly from the rmarkdown package.

Whichever way you choose, this will be the output obtained:

We now have to see how to share this with Mr. Clough.

Sharing an R Markdown report

The alternatives available to share R Markdown documents are basically two:

  • Static R Markdown reports: If the document encompasses only static elements, you can render it in different file formats, such as .html, .pdf, or even Word. Be aware that in order to create such a kind of document, you need to select Document from the New R Markdown window. Let me show...