Written by leaders in the data mining community, including the developers of the RapidMiner software, this book 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 book and software tools cover all relevant steps of the data mining process. The software and their extensions can be freely downloaded at www.RapidMiner.com.
Written by leaders in the data mining community, including the developers of the RapidMiner software, this book 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 book and software tools cover all relevant steps of the data mining process. The software and their extensions can be freely downloaded at www.RapidMiner.com.
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.
Inhaltsangabe
Introduction to Data Mining and RapidMiner. Basic Classification Use Cases for Credit Approval and in Education. Marketing Cross-Selling and Recommender System Use Cases. Clustering in Medical and Educational Domains. Text Mining: Spam Detection Language Detection and Customer Feedback Analysis. Feature Selection and Classification in Astroparticle Physics and in Medical Domains. Molecular Structure- and Property-Activity Relationship Modeling in Biochemistry and Medicine. Image Mining: Feature Extraction Segmentation and Classification. Anomaly Detection Instance Selection and Prototype Construction. Meta-Learning Automated Learner Selection Feature Selection and Parameter Optimization. Index.
Introduction to Data Mining and RapidMiner. Basic Classification Use Cases for Credit Approval and in Education. Marketing Cross-Selling and Recommender System Use Cases. Clustering in Medical and Educational Domains. Text Mining: Spam Detection Language Detection and Customer Feedback Analysis. Feature Selection and Classification in Astroparticle Physics and in Medical Domains. Molecular Structure- and Property-Activity Relationship Modeling in Biochemistry and Medicine. Image Mining: Feature Extraction Segmentation and Classification. Anomaly Detection Instance Selection and Prototype Construction. Meta-Learning Automated Learner Selection Feature Selection and Parameter Optimization. Index.
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