Exploring Data with RapidMiner

More Information
Learn
  • Import real data from files in multiple formats and from databases
  • Extract features from structured and unstructured data
  • Restructure, reduce, and summarize data to help you understand it more easily and process it more quickly
  • Visualize data in new ways to help you understand it
  • Detect outliers and methods to handle them
  • Detect missing data and implement ways to handle it
  • Understand resource constraints and what to do about them
About

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.

Features
  • See how to import, parse, and structure your data quickly and effectively
  • Understand the visualization possibilities and be inspired to use these with your own data
  • Structured in a modular way to adhere to standard industry processes
Page Count 162
Course Length 4 hours 51 minutes
ISBN 9781782169338
Date Of Publication 25 Nov 2013

Authors

Andrew Chisholm

Andrew Chisholm completed his degree in Physics from Oxford University nearly thirty years ago. This coincided with the growth in software engineering and it led him to a career in the IT industry. For the last decade he has been very involved in mobile telecommunications, where he is currently a product manager for a market-leading test and monitoring solution used by many mobile operators worldwide._x000D_ _x000D_ Throughout his career, he has always maintained an active interest in all aspects of data. In particular, he has always enjoyed finding ways to extract value from data and presenting this in compelling ways to help others meet their objectives. Recently, he completed a Master's in Data Mining and Business Intelligence with first class honors. He is a certified RapidMiner expert and has been using this product to solve real problems for several years. He maintains a blog where he shares some miscellaneous helpful advice on how to get the best out of RapidMiner._x000D_ _x000D_ He approaches problems from a practical perspective and has a great deal of relevant hands-on experience with real data. This book draws this experience together in the context of exploring data—the first and most important step in a data mining_x000D_ process._x000D_ _x000D_ He has published conference papers relating to unsupervised clustering and cluster validity measures and contributed a chapter called Visualizing cluster validity measures to an upcoming book entitled RapidMiner: Use Cases and Business Analytics Applications, Chapman & Hall/CRC_x000D_