RapidMiner (eBook, PDF)

Data Mining Use Cases and Business Analytics Applications
Redaktion: Hofmann, Markus; Klinkenberg, Ralf

• Format: PDF

Produktbeschreibung

Powerful, Flexible Tools for a Data-Driven WorldAs 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 incre

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 525
• Erscheinungstermin: 19. April 2016
• Englisch
• ISBN-13: 9781482205503
• Artikelnr.: 40391296

Autorenporträt

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.