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Bertrand Kerautret. Web Information Systems and Technologies. Karl-Heinz Krempels. This book presents new intelligent data management methods and tools, including new results from the field of inference. Leading experts also map out future directions of intelligent data analysis. This book will be a valuable reference for researchers exploring the interdisciplinary area between statistics and computer science as well as for professionals applying advanced data analysis methods in industry.
Convert currency. Add to Basket. Book Description Springer. Condition: New. Seller Inventory More information about this seller Contact this seller. First edition. Data analysis and inference have traditionally been research areas of statistics. However, the need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new methods and tools, new types of databases, new efficient algorithms, new data structures, etc.
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This monograph presents new intelligent data management methods and tools, such as the support vector machine, and new results from the field of inference, in particular of causal modeling. In 11 well-structured chapters, leading experts map out the major tendencies and future directions of intelligent data analysis. The book will become a valuable source of reference for researchers exploring the interdisciplinary area between statistics and computer science as well as for professionals applying advanced data analysis methods in industry and commerce. Students and lecturers will find the book useful as an introduction to the area.
Printed Pages: How do you know? How do we know if X caused Y? What are the causes of a given phenomena?source site
Causal Models and Intelligent Data Management - kercwordfunthe.tk
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- Causal Models and Intelligent Data Management.
Published on Feb View 26 Download 0. Example of insulating my house this past winter What caused the decline in these 6 diseases in developing countries? Causal Networks Denny Borsboom. Overview The causal relation Causality and conditional independence Causal networks Blocking and d-separation Excercise Documents.