Probabilistic Methods for Financial and Marketing Informatics - Hardcover

Neapolitan, Richard E.; Jiang, Xia

9780123704771: Probabilistic Methods for Financial and Marketing Informatics

Hardcover

ISBN 10: 0123704774 ISBN 13: 9780123704771

Publisher: Morgan Kaufmann, 2007

Probabilistic Methods for Financial and Marketing Informatics aims to provide students with insights and a guide explaining how to apply probabilistic reasoning to business problems. Rather than dwelling on rigor, algorithms, and proofs of theorems, the authors concentrate on showing examples and using the software package Netica to represent and solve problems.

The book contains unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance. It shares insights about when and why probabilistic methods can and cannot be used effectively.

This book is recommended for all R&D professionals and students who are involved with industrial informatics, that is, applying the methodologies of computer science and engineering to business or industry information. This includes computer science and other professionals in the data management and data mining field whose interests are business and marketing information in general, and who want to apply AI and probabilistic methods to their problems in order to better predict how well a product or service will do in a particular market, for instance.

Typical fields where this technology is used are in advertising, venture capital decision making, operational risk measurement in any industry, credit scoring, and investment science.

Unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance
Shares insights about when and why probabilistic methods can and cannot be used effectively
Complete review of Bayesian networks and probabilistic methods for those IT professionals new to informatics.

"synopsis" may belong to another edition of this title.

Review:

"One of the features I appreciate most is that almost all the examples refer to real-world situations, which is especially useful because it shows how to build probabilistic models for other domains." --Francisco Diez, UNED, Madrid, Spain

Synopsis:

Bayesian Networks are a form of probabilistic graphical models and they are used for modeling knowledge in many application areas, from medicine to image processing. They are particularly useful for business applications. This book provides unique coverage of probabilistic reasoning topics applied to business problems, including marketing, banking, operations management, and finance. It shares insights about when and why probabilistic methods can and cannot be used effectively. It also provides complete review of Bayesian networks and probabilistic methods for those IT professionals new to informatics.

"About this title" may belong to another edition of this title.