Verlag: CRC Press 2021-07-29, Boca Raton, 2021
ISBN 10: 0367366517 ISBN 13: 9780367366513
Anbieter: Blackwell's, London, Vereinigtes Königreich
hardback. Zustand: New. Language: ENG.
Verlag: CRC Press 2023-03-31, Boca Raton, 2023
ISBN 10: 0367263505 ISBN 13: 9780367263508
Anbieter: Blackwell's, London, Vereinigtes Königreich
hardback. Zustand: New. Language: ENG.
Verlag: Chapman and Hall/CRC, 2021
ISBN 10: 0367366517 ISBN 13: 9780367366513
Anbieter: Monster Bookshop, Fleckney, Vereinigtes Königreich
Hardcover. Zustand: New. BRAND NEW ** SUPER FAST SHIPPING FROM UK WAREHOUSE ** 30 DAY MONEY BACK GUARANTEE.
Verlag: Apple Academic Press Inc., Canada, Oakville, 2014
ISBN 10: 1482225581 ISBN 13: 9781482225587
Anbieter: WorldofBooks, Goring-By-Sea, WS, Vereinigtes Königreich
Paperback. Zustand: Very Good. Understand the Foundations of Bayesian NetworksCore Properties and Definitions Explained Bayesian Networks: With Examples in R introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples in R illustrate each step of the modeling process. The examples start from the simplest notions and gradually increase in complexity. The authors also distinguish the probabilistic models from their estimation with data sets. The first three chapters explain the whole process of Bayesian network modeling, from structure learning to parameter learning to inference. These chapters cover discrete Bayesian, Gaussian Bayesian, and hybrid networks, including arbitrary random variables. The book then gives a concise but rigorous treatment of the fundamentals of Bayesian networks and offers an introduction to causal Bayesian networks. It also presents an overview of R and other software packages appropriate for Bayesian networks. The final chapter evaluates two real-world examples: a landmark causal protein signaling network paper and graphical modeling approaches for predicting the composition of different body parts. Suitable for graduate students and non-statisticians, this text provides an introductory overview of Bayesian networks. It gives readers a clear, practical understanding of the general approach and steps involved. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Verlag: CRC Press, 2021
ISBN 10: 0367366517 ISBN 13: 9780367366513
Anbieter: moluna, Greven, Deutschland
Gebunden. Zustand: New. Marco Scutari is a Senior Lecturer at Istituto Dalle Molle di Studisull Intelligenza Artificiale (IDSIA), Switzerland. He has held positions in Statistics, Statistical Genetics and Machine Learning in the UK and Switzerland since complet.