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Learning from Data
Language: en
Pages: 450
Authors: Doug Fisher, Hans-J. Lenz, Hans-J Lenz
Categories: Computers
Type: BOOK - Published: 1996-05-02 - Publisher: Springer Science & Business Media

This volume contains a revised collection of papers originally presented at the Fifth International Workshop on Artificial Intelligence and Statistics in 1995. The topics represented in this volume are diverse, and include natural language application causality and graphical models, classification, learning, knowledge discovery, and exploratory data analysis. The chapters illustrate
Utility-Based Learning from Data
Language: en
Pages: 417
Authors: Craig Friedman, Sven Sandow
Categories: Business & Economics
Type: BOOK - Published: 2016-04-19 - Publisher: CRC Press

Utility-Based Learning from Data provides a pedagogical, self-contained discussion of probability estimation methods via a coherent approach from the viewpoint of a decision maker who acts in an uncertain environment. This approach is motivated by the idea that probabilistic models are usually not learned for their own sake; rather, they
Learning from Data
Language: en
Pages:
Authors: IntroBooks Team
Categories: Computers
Type: BOOK - Published: - Publisher: IntroBooks

Learning from Data is the concept which has developed recently. Data is a concept which is raw in nature and it has been given meaning only after compilation and currently, after globalization. The amount of data in all the sectors have grown enormously. Learning from Data is a very popular
Learning From Data
Language: en
Pages: 580
Authors: Arthur Glenberg, Matthew Andrzejewski, Herman Fernando, Jas Kalsi, Asif Muneer, Hashim Ahmed
Categories: Education
Type: BOOK - Published: 2007-08-09 - Publisher: Routledge

Learning from Data focuses on how to interpret psychological data and statistical results. The authors review the basics of statistical reasoning to helpstudents better understand relevant data that affecttheir everyday lives.Numerous examples based on current research and events are featured throughout.To facilitate learning, authors Glenberg and
Learning from Data
Language: en
Pages: 560
Authors: Vladimir Cherkassky, Filip M. Mulier
Categories: Computers
Type: BOOK - Published: 2007-09-10 - Publisher: John Wiley & Sons

An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that