Exploring Data with RapidMiner

by Andrew Chisholm

In Detail

Data is everywhere and the amount is increasing so much that the gap between what people can understand and what is available is widening relentlessly. There is a huge value in data, but much of this value lies untapped. 80% of data mining is about understanding data, exploring it, cleaning it, and structuring it so that it can be mined. RapidMiner is an environment for machine learning, data mining, text mining, predictive analytics, and business analytics. It is used for research, education, training, rapid prototyping, application development, and industrial applications.

Exploring Data with RapidMiner is packed with practical examples to help practitioners get to grips with their own data. The chapters within this book are arranged within an overall framework and can additionally be consulted on an ad-hoc basis. It provides simple to intermediate examples showing modeling, visualization, and more using RapidMiner.

Exploring Data with RapidMiner is a helpful guide that presents the important steps in a logical order. This book starts with importing data and then lead you through cleaning, handling missing values, visualizing, and extracting additional information, as well as understanding the time constraints that real data places on getting a result. The book uses
real examples to help you understand how to set up processes, quickly.

This book will give you a solid understanding of the possibilities that RapidMiner gives for exploring data and you will be inspired to use it for your own work.

Approach

A step-by-step tutorial style using examples so that users of different levels will benefit from the facilities offered by RapidMiner.

Who this book is for

If you are a computer scientist or an engineer who has real data from which you want to extract value, this book is ideal for you. You will need to have at least a basic awareness of data mining techniques and some exposure to RapidMiner.

150 pages, Kindle Edition

First published November 25, 2013

Reviews

[Neal Rauhauser]

This is the second book I've reviewed for Packt Publishing and I really like it. I am an old unix guy, used to piping commands in the shell, and I was immediately intrigued the first time I saw RapidMiner's process flow. As there was no written guide on the basics, I could follow examples from YouTube, but not understand and apply the tool to my own problems. I am starting my second pass through the book, this time using some data from a problem I've been wrestling with myself rather than the examples.

This book would be a good choice for a IT person with LAMP stack or other SQL background who has been asked to support a RapidMiner install, as there is performance tuning information, but I think where it would really shine are for those who come from a business analysis perspective who have not experienced the unix command chaining functions. RapidMiner does this in a sensible fashion with a graphical process design environment.

As for professional development I think this is a winner - RapidMiner is best of breed in this area, they just got a round of funding, and it's a good bullet point for one's resume. The book uses the 5.3 version of the software, both the standalone client and optional remote server are free to download.

[Manuel Garcia Lacayo · Rating 4 out of 5]

I'm mainly interested in outliers and I have found chapter 5 (outliers) very helpful, chapter 3 (visualization) and chapter 6 (missing values) are also worth to read. I'm glad to realize that I can use Groovy on RapidMiner (I didn't know it) and I'm looking forward to test the sample scripts.