Includes bibliographical references and index.

1. Introduction to data mining and RapidMiner -- 2. Basic classification use cases for credit approval and in education -- 3. Marketing, cross-selling, and recommender system use cases -- 4. Clustering in medical and educational domains -- 5. Text mining : spam detection, language detection, and customer feedback analysis -- 6. Feature selection and classification in astroparticle physics and in medical domains -- 7. Molecular structure- and property-activity relationship modeling in biochemistry and medicine -- 8. Image mining : feature extraction, segmentation, and classification -- 9. Anomaly detection, instance selection, and prototype construction -- 10. Meta-learning, automated learner selection, feature selection, and parameter optimization.

"RapidMiner is one of the most widely used open source data mining solutions world-wide. This book provides an application use case-based introduction to data mining and to RapidMiner (and RapidAnalytics.) It presents many different applications of data mining and how to implement them with RapidMiner, and it allows readers to get started with their own data mining applications with RapidMiner, or other similar tools. The software, the data sets, and RapidMiner data mining processes used and discussed in the book are made available to readers"-- Provided by publisher.

Also available in print format.