- Hardcover: 400 pages
- Publisher: Morgan Kaufmann (22 May 2009)
- Language English
- ISBN-10: 0123704766
- ISBN-13: 978-0123704764
- Product Dimensions: 23.6 x 19 x 2.8 cm
- Average Customer Review: 2.0 out of 5 stars See all reviews (1 customer review)
- Amazon Bestsellers Rank: 1,125,396 in Books (See Top 100 in Books)
Probabilistic Methods for Bioinformatics
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Product Description
Review
"Probabilistic Methods for Financial and Marketing Informatics makes important and novel contributions to understanding investment strategies and should be welcomed by practitioners and researchers alike" --Tony Volpon, Strategist/Chief Economist, CM Capital Markets "Richard Neapolitan's new book with Xia Jiang on Bayes nets and its applications to finance and marketing is a must-read for professionals in the finance and marketing communities. The relatively new technique of Bayes nets has great potential for managing uncertainty in all domains. But applications of this technique in finance and marketing have not been widely reported to date. This new book fills this gaping void at a level most professionals can easily understand. Congratulations to Neapolitan and Jiang for this excellent addition to the literature on Bayes nets!" --Prakash P. Shenoy, University of Kansas
Product Description
The Bayesian network is one of the most important architectures for representing and reasoning with multivariate probability distributions. When used in conjunction with specialized informatics, possibilities of real-world applications are achieved. "Probabilistic Methods for Financial and Marketing Informatics" covers two of the most important applications of informatics and concentrates on approaches to solving realistic business problems. This book provides applications of informatics to areas such as managerial options and decision making, investment science, marketing, and data mining, concentrating on the probabilistic and decision-theoretic approaches to informatics, emphasizing the use of Bayesian networks. Rather than dwelling on rigor, algorithms, and proofs of theorems, the authors focus on problem solving and practical applications. Included in this book are ample examples and exercises throughout, as well as six chapters that each walk through pragmatic situations. In many cases, solutions are expanded, as the authors discuss their final implementation using the software package Netica. Features of this title are as mentioned below. It features unique coverage of probabilistic reasoning topics applied to business problems, including advertising, market basket analysis, venture capital decision making, operational risk measurement, bankruptcy prediction, and investment science. It shares insights about when and why probabilistic methods can and cannot be used effectively. It provides complete review of Bayesian networks and probabilistic methods for those IT professionals new to probabilistic informatics. It presents unique coverage of probabilistic reasoning methods applied to bioinformatics data - those methods that are likely to become the standard analysis tools for bioinformatics. It offers complete review of Bayesian networks and probabilistic methods with a practical approach.
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Customer Reviews
Most Helpful Customer Reviews
Format:Hardcover
The book overlaps for over 50% with the previous book by the same author
"Learning Bayesian Networks".
"Learning Bayesian Networks".
Most Helpful Customer Reviews on Amazon.com (beta)
Amazon.com:
1 review
5 of 6 people found the following review helpful
Lots of examples
7 Nov 2009
Format:Hardcover|Amazon Verified Purchase
This book really helps in bridging formalism to understanding by providing lots of examples and walking through the examples. It's a pleasure to read.
One can skim what seems basic. But if something is not clear, one can work through a few examples. It's strength is pedagogical.
One can skim what seems basic. But if something is not clear, one can work through a few examples. It's strength is pedagogical.
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