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Powerful, Flexible Tools for a Data-Driven World
As the data deluge continues in today’s world, the need to master data mining, predictive analytics, and business analytics has never been greater. These techniques and tools provide unprecedented insights into data, enabling better decision making and forecasting, and ultimately the solution of increasingly complex problems.
Learn from the Creators of the RapidMiner Software
Written by leaders in the data mining community, including the developers of the RapidMiner software, RapidMiner: Data Mining Use Cases and Business Analytics Applications provides an in-depth introduction to the application of data mining and business analytics techniques and tools in scientific research, medicine, industry, commerce, and diverse other sectors. It presents the most powerful and flexible open source software solutions: RapidMiner and RapidAnalytics. The software and their extensions can be freely downloaded at www.RapidMiner.com.
Understand Each Stage of the Data Mining Process
The book and software tools cover all relevant steps of the data mining process, from data loading, transformation, integration, aggregation, and visualization to automated feature selection, automated parameter and process optimization, and integration with other tools, such as R packages or your IT infrastructure via web services. The book and software also extensively discuss the analysis of unstructured data, including text and image mining.
Easily Implement Analytics Approaches Using RapidMiner and RapidAnalytics
Each chapter describes an application, how to approach it with data mining methods, and how to implement it with RapidMiner and RapidAnalytics. These application-oriented chapters give you not only the necessary analytics to solve problems and tasks, but also reproducible, step-by-step descriptions of using RapidMiner and RapidAnalytics. The case studies serve as blueprints for your own data mining applications, enabling you to effectively solve similar problems.
- Sales Rank: #791778 in Books
- Brand: Brand: Chapman and Hall/CRC
- Published on: 2013-10-25
- Original language: English
- Number of items: 1
- Dimensions: 10.10" h x 1.30" w x 7.00" l, 2.40 pounds
- Binding: Hardcover
- 525 pages
- Used Book in Good Condition
Review
In this book, case studies communicate how to analyze databases, text collections, and image data. … How the given data are transformed to meet the requirements of the method is illustrated by screenshots of RapidMiner. The RapidMiner processes and datasets described in the case studies are published on the companion web page of this book. The inspiring applications may be used as a blueprint and a justification of future applications.
―Professor Dr. Katharina Morik, Technical University of Dortmund
Hofmann and Klinkenberg have produced a fine collection of essays on data mining and analytic models, presented in several cross-disciplinary cases. This book describes data mining and case applications using Rapidminer models and analytic techniques. ... The book represents the work of more than 30 contributors. Managing the writing styles of so many contributors is a challenging task, and the editors are to be commended for their effort. The material flows well, is very readable, and easily transitions from chapter to chapter and section to section. The book is divided into ten sections, each focusing on a different disciplinary area and a different analytic and mining model. Each section includes one or more cases. .. This is a good book. If you are interested in some very interesting data mining cases, or if you would like to learn Rapidminer, it will not disappoint. The bibliographic references are lengthy and the indices are well done.
―Book review appearing in ACM Computing Reviews, March 2014
About the Author
Markus Hofmann is a lecturer at the Institute of Technology Blanchardstown, where he focuses on data mining, text mining, data exploration and visualization, and business intelligence. Dr. Hofmann is a member of the Register of Expert Panellists of the Irish Higher Education and Training Awards council, an external examiner to two other third-level institutes, and a specialist in undergraduate and postgraduate course development. He received his PhD from Trinity College Dublin.
Ralf Klinkenberg is the co-founder of Rapid-I and CBDO of Rapid-I Germany. Rapid-I is the company behind the open source software solution RapidMiner and its server version RapidAnalytics. Mr. Klinkenberg has more than 15 years of consulting and training experience in data mining and RapidMiner-based solutions. He received his MS in computer science from the Technical University of Dortmund and Missouri University of Science and Technology.
Most helpful customer reviews
8 of 8 people found the following review helpful.
Excellent, but…..
By JoeT
Rapidminer is a great tool, but to me, suffered from abysmal documentation.
So, when Matthew North came out with "Data Mining for the Masses", I was both happy (great explanations in all the chapters) and hoping that he would release a second version of his book. So far, no.
Instead, this book was published. It is edited by Markus Hofmann, and contains 24-chapters which were cobbled together from outside sources. So, I was expecting something similar to North's book.
Not quite.
Pros:
1. 24 (actually 23 if you don't count the introductory chapter) fairly detailed use cases for a number of different projects.
2. All of the processes can be found on the rapidminerbook.com site.
3. Advanced use of Rapidminer. Personally, I think a bit of overkill for beginners but experienced uses will love the examples.
Cons:
1. The book to me is a series of 23-use cases. They define the problem and offer the process diagram then stop. Most of the chapters do not even discuss what happens if you execute the process and explain how to interpret the results. This is what is significantly different from North, and if you are using a process that you are unfamiliar with, isn't a good thing.
2. The editor was lazy. Instead of creating 1-zip file with all the processes in it, labeled by chapter, there are 24-different files to download from the website. And, some are labeled "Chapter 12" or something altogether different.
3. Some of the data files that the processes seem to need are missing and I have had difficulty in getting the same results on some of the processes. One of the processes is just plain wrong (it's right in the book though), and Chapter 17…still can't get it to work.
Summary:
This book does quite a nice job in the "define and design" part of creating a process. I can't imagine that anyone taking the time to work through the examples will not learn something. However, I caution a beginner using Rapidminer: this book might be a bit of overkill as a first book. You would best use North's book first, get some experience, then go through this book, since the 'analysis' component of this book is missing from most of the chapters.
5 of 5 people found the following review helpful.
Wonderful Case Studies!
By Mehul Shah
Wow, this is truly a great book. The 20+ case studies in this book are stupendous in breadth and scope spawning numerous domains; retail, healthcare and pharmaceutical to name a few. RapidMiner is well known for providing a data-mining platform that makes data-mining accessible to everyone, including those not blessed with having gone through the rigors of a PhD in knowledge discovery.
This book provides the much needed impetus to jumpstart serious data-mining initiatives by first systematically dissecting the challenges and hurdles to data-mining in the real world and subsequently providing fully operational RapidMiner solutions a.k.a. processes to tame the challenges. Solutions are also provided for the much more difficult challenges of text mining, image mining and anomaly detection.
The lessons learnt are easily extensible to the unique challenges we are called upon to solve in our corner of the world. I heartily recommend this book-two thumbs up!
5 of 5 people found the following review helpful.
Great book, waiting more books from the editors and authors of this work
By spssspss
There are many authors in the book and they show their expertise in different kinds of algorithms so you have a chance to witness different logical processes that may help you at your own data mining journey, you should study with the data sets together while studying the book and examples helps you concrete your knowledge, The best thing about the book for me is this book is not just about rapidminer although it seems like a software training book it also gives you information about the data mining thinking, The editor Markus Hofmann also helped me so much when i had questions about some of the section, he is an expert and reply my mails in minutes, Lastly this book is only book that is serious and helpful about rapidminer, other documentation on rapidminer helped me but deep understanding became possible with this book, thanks to authors who contributed the writing of the section, i am waiting more books from Markus Hofmann.
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