Computational Learning Probabilistic Reasoning (20 results)

Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Hardcover. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

Condition: Very Good. Text block firm and clean, binding unblemished, boards straight, without highlights or underlining. Very clean, nearly like new. Without any discs, access codes or extra items. Previous library copy with usual markings/stickers or stamps. Supporting Bay Area Friends of the Library since 2010. Well packaged and promptly shipped.…

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

Condition: new.

Condition: New.

Condition: New. In English.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Condition: New.

Brossura. Condition: fine. West Sussex, 1996; pp. 312. Libro.

Condition: New. pp. 338.

Condition: New. This text is devoted to two interrelated techniques used in solving some important problems in machine intelligence and pattern recognition. Editor(s): Gammerman, A. Num Pages: 338 pages, Illustrations. BIC Classification: PBT; UYA; UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 257 x 183 x 25. Weight in Grams: 776. . 1996. 1st Edition. Hardcover. . . . . …

Condition: New. pp. 338.

Hardcover. Condition: Brand New. 1st edition. 338 pages. 10.00x7.00x1.00 inches. In Stock.

Condition: New. This text is devoted to two interrelated techniques used in solving some important problems in machine intelligence and pattern recognition. Editor(s): Gammerman, A. Num Pages: 338 pages, Illustrations. BIC Classification: PBT; UYA; UYQM. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 257 x 183 x 25. Weight in Grams: 776. . 1996. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. …

Hardcover. Condition: new. Hardcover. Providing a unified coverage of the latest research and applications methods and techniques, this book is devoted to two interrelated techniques for solving some important problems in machine intelligence and pattern recognition, namely probabilistic reasoning and computational learning. The contributions in this volume describe and explore the current developments in computer science and theoretical statistics which provide computational probabilistic models for manipulating knowledge found in industrial and business data. These methods are very efficient for handling complex problems in medicine, commerce and finance. Part I covers Generalisation Principles and Learning and describes several new inductive principles and techniques used in computational learning. Part II describes Causation and Model Selection including the graphical probabilistic models that exploit the independence relationships presented in the graphs, and applications of Bayesian networks to multivariate statistical analysis. Part III includes case studies and descriptions of Bayesian Belief Networks and Hybrid Systems. Finally, Part IV on Decision-Making, Optimization and Classification describes some related theoretical work in the field of probabilistic reasoning. Statisticians, IT strategy planners, professionals and researchers with interests in learning, intelligent databases and pattern recognition and data processing for expert systems will find this book to be an invaluable resource. Real-life problems are used to demonstrate the practical and effective implementation of the relevant algorithms and techniques. This text is devoted to two interrelated techniques used in solving some important problems in machine intelligence and pattern recognition. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Hardcover. Condition: Brand New. 1st edition. 338 pages. 10.00x7.00x1.00 inches. In Stock. This item is printed on demand.