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Bayesian Networks and Decision Graphs

Posted By: AvaxGenius
Bayesian Networks and Decision Graphs

Bayesian Networks and Decision Graphs by Finn V. Jensen
English | PDF | 2001 | 279 Pages | ISBN : N/A | 19.7 MB

Bayesian networks and decision graphs are formal graphical languages for representation and communication of decision scenarios requiring reasoning under uncertainty. Their strengths are two-sided. It is easy for humans to construct and to understand them, and when communicated to a computer, they can easily be compiled. Furthermore, handy algorithms are developed for analyses of the models and for providing responses to a wide range of requests such as belief updating, determining optimal strategies, conflict analyses of evidence, and most probable explanation. The book emphasizes both the human and the computer sides. Part I gives a thorough introduction to Bayesian networks as well as decision trees and infulence diagrams, and through examples and exercises, the reader is instructed in building graphical models from domain knowledge.

Bayesian Networks: A Practical Guide to Applications

Posted By: AvaxGenius
Bayesian Networks: A Practical Guide to Applications

Bayesian Networks: A Practical Guide to Applications by Dr Olivier Pourret, Patrick Naim, Dr Bruce Marcot
English | PDF | 2008 | 433 Pages | ISBN : 0470060301 | 12.2 MB

Bayesian Networks, the result of the convergence of artificial intelligence with statistics, are growing in popularity. Their versatility and modelling power is now employed across a variety of fields for the purposes of analysis, simulation, prediction and diagnosis.

"Information Systems: A Global Perspective. Contemporary Issues" ed. by Denis Reilly

Posted By: exLib
"Information Systems: A Global Perspective. Contemporary Issues" ed. by Denis Reilly

"Information Systems: A Global Perspective. Contemporary Issues" ed. by Denis Reilly
ITexLi | 2022 | ISBN: 1839694645 9781839694646 1839694637 9781839694639 1839694653 9781839694653 | 80 pages | PDF | 6 MB

This book brings together a collection of research papers related to the application of Information technology (IT) and Information systems (IS) to address issues at national levels.

Neural Information Processing (Repost)

Posted By: AvaxGenius
Neural Information Processing (Repost)

Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part III By Derong Liu
English | PDF | 2017 | 953 Pages | ISBN : 3319700898 | 207.7 MB

The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions.

Bayesian Networks in R: with Applications in Systems Biology (Repost)

Posted By: AvaxGenius
Bayesian Networks in R: with Applications in Systems Biology (Repost)

Bayesian Networks in R: with Applications in Systems Biology by Radhakrishnan Nagarajan
English | PDF | 2013 | 168 Pages | ISBN : 1461464455 | 2.1 MB

Bayesian Networks in R with Applications in Systems Biology introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is gradually increased across the chapters with exercises and solutions for enhanced understanding and hands-on experimentation of key concepts. Applications focus on systems biology with emphasis on modeling pathways and signaling mechanisms from high throughput molecular data.

Bayesian Networks in R: with Applications in Systems Biology

Posted By: AvaxGenius
Bayesian Networks in R: with Applications in Systems Biology

Bayesian Networks in R: with Applications in Systems Biology by Radhakrishnan Nagarajan
English | PDF | 2013 | 168 Pages | ISBN : 1461464455 | 2.1 MB

Bayesian Networks in R with Applications in Systems Biology introduces the reader to the essential concepts in Bayesian network modeling and inference in conjunction with examples in the open-source statistical environment R. The level of sophistication is gradually increased across the chapters with exercises and solutions for enhanced understanding and hands-on experimentation of key concepts. Applications focus on systems biology with emphasis on modeling pathways and signaling mechanisms from high throughput molecular data.

Neural Information Processing (Repost)

Posted By: AvaxGenius
Neural Information Processing (Repost)

Neural Information Processing: 24th International Conference, ICONIP 2017, Guangzhou, China, November 14-18, 2017, Proceedings, Part III By Derong Liu
English | PDF | 2017 | 953 Pages | ISBN : 3319700898 | 207.7 MB

The six volume set LNCS 10634, LNCS 10635, LNCS 10636, LNCS 10637, LNCS 10638, and LNCS 10639 constitues the proceedings of the 24rd International Conference on Neural Information Processing, ICONIP 2017, held in Guangzhou, China, in November 2017. The 563 full papers presented were carefully reviewed and selected from 856 submissions.

Development of Clinical Decision Support Systems using Bayesian Networks: With an example of a Multi-Disciplinary Treatm

Posted By: roxul
Development of Clinical Decision Support Systems using Bayesian Networks: With an example of a Multi-Disciplinary Treatm

Mario A. Cypko, "Development of Clinical Decision Support Systems using Bayesian Networks: With an example of a Multi-Disciplinary Treatm"
English | ISBN: 3658325933 | 2020 | 148 pages | PDF | 6 MB