Gabor Bakos - KNIME Essentials
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Copyright 2013 Packt Publishing
All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews.
Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty, either express or implied. Neither the author, nor Packt Publishing, and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book.
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals. However, Packt Publishing cannot guarantee the accuracy of this information.
First published: October 2013
Production Reference: 1101013
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-84969-921-1
www.packtpub.com
Cover Image by Abhishek Pandey (<>)
Author
Gbor Bakos
Reviewers
Thorsten Meinl
Takeshi Nakano
Acquisition Editors
Saleem Ahmed
Edward Gordon
Commissioning Editor
Amit Ghodake
Technical Editors
Iram Malik
Aman Preet Singh
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Graphics
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Production Coordinator
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Cover Work
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Gbor Bakos is a programmer and a mathematician, having a few years of experience with KNIME and KNIME node development (HiTS nodes and RapidMiner integration for KNIME).
In Trinity College, Dublin, the author was helping a research group with his data analysis skills (also had the opportunity to improve those), and with the new KNIME node development. When he worked for the evopro Kft. or the Scriptum Informatika Zrt., he was also working on various data analysis software products. He currently works for his own company, Mind Eratosthenes Kft. (www.mind-era.com), where he develops the RapidMiner integration for KNIME (tech.knime.org/community/rapidminer-integration), among other things.
The author would like to thank the reviewers and Packt Publishing for their help in creating this book.
Thorsten Meinl is currently a Senior Software Developer at KNIME.com in Zurich. He holds a PhD in Computer Science from the University of Konstanz. He has been working on KNIME for over seven years. His main responsibilities are quality assurance, testing, and the continuous integration infrastructure, as well as managing the KNIME Community Contributions. Besides this, he is also interested in parallel computing and cheminformatics.
Takeshi Nakano is a Senior Research Engineer working for Recruit Technologies Co., Ltd. and leads the Advanced Technology Lab in Japan. He holds a Master's degree from the Nara Institute of Science and Technology (NAIST) in Computer Science. He is the lead author of Hadoop Hacks, a book from O'Reilly Japan, and also the author of Getting Started with Apache Solr, a book from GijutsuHyohron in Japan. He loves to find inspiration for his hobbies (reading, scuba diving, and others).
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Dear reader, welcome to an intuitive way of data analysis. Using a visual programming language based on dataflows, you can create an easy-to-understand analysis process, while it internally checks signals about some of the common problems. Obviously, any environment that does not help with proper documentation would be destined to fail, but KNIME's success is based not just on its high qualitycross-platformcode, but also on the good description about what it does and how you can use the building blocks.
This book covers the most common tasks that are required during the data preparation and visualization phase of data analysis using KNIME. Because of the size constraintsand to bring the best price/value for those who are already familiar with or not interested in modelingwe have not covered the modeling and machine learning algorithms available for KNIME. If you are already familiar with these algorithms, you will easily get familiar with the options in KNIME, and these are quite obvious to use, so you lose almost nothing. If you have not found time yet to get acquainted with these concepts, we encourage you to first learn for what these procedures are good and when you should use them. There are some good books, courses, and training availablethese are the ideal options for learningbut the Wikipedia articles can also give you a basic introduction specific to the algorithm you want to use.
, Installation and Using KNIME , introduces the user interface, the concepts used in the first three chapters, and how you can install and configure KNIME and its extensions.
, Data Preprocessing , covers the most common tasks, so that you can analyze your data, such as loading, transforming, and generating data; it also introduces the powerful regular expressions and some case studies.
, Data Exploration , describes how you can use KNIME to get an overview about your data, how you can visualize them in different forms, or even create publication quality figures.
, Reporting , introduces the KNIME reporting extension with the specific concepts, the user interface, and the basic blocks of reports.
You only need a KNIME-compatible operating system, which is either a modern Linux, Mac OS X (10.6 or above), or Windows XP or above. The Java runtime is bundled with KNIME, and the first chapter describes how you can download and install KNIME. For this reason, you will need Internet connection too.
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