Causal Models and Intelligent Data Management (eBook, PDF)

Redaktion: Gammerman, Alex

• Format: PDF

Produktbeschreibung

The need to electronically store, manipulate and analyze large-scale, high-dimensional data sets requires new computational methods. 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.

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Produktdetails

• Verlag: Springer Berlin Heidelberg
• Seitenzahl: 185
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9783642586484
• Artikelnr.: 52956705

Inhaltsangabe

I. Causal Models.- 1. Statistics, Causality, and Graphs.- 2. Causal Conjecture.- 3. Who Needs Counterfactuals?.- 4. Causality: Independence and Determinism.- II. Intelligent Data Management.- 5. Intelligent Data Analysis and Deep Understanding.- 6. Learning Algorithms in High Dimensional Spaces.- 7. Learning Linear Causal Models by MML Sampling.- 8. Game Theory Approach to Multicommodity Flow Network Vulnerability Analysis.- 9. On the Accuracy of Stochastic Complexity Approximations.- 10. AI Modelling for Data Quality Control Xiaohui Liu.- 11. New Directions in Text Categorization.