menu
{ "item_title" : "Advances in Bayesian Networks", "item_author" : [" José a. Gámez", "Serafin Moral", "Antonio Salmerón Cerdan "], "item_description" : "In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as artificial intelligence and statistics. This carefully edited monograph is a compendium of the most recent advances in the area of probabilistic graphical models such as decision graphs, learning from data and inference. It presents a survey of the state of the art of specific topics of recent interest of Bayesian Networks, including approximate propagation, abductive inferences, decision graphs, and applications of influence. In addition, Advances in Bayesian Networks presents a careful selection of applications of probabilistic graphical models to various fields such as speech recognition, meteorology or information retrieval.", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/3/54/020/876/3540208763_b.jpg", "price_data" : { "retail_price" : "109.99", "online_price" : "109.99", "our_price" : "109.99", "club_price" : "109.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Advances in Bayesian Networks|José a. Gámez

Advances in Bayesian Networks

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

In recent years probabilistic graphical models, especially Bayesian networks and decision graphs, have experienced significant theoretical development within areas such as artificial intelligence and statistics. This carefully edited monograph is a compendium of the most recent advances in the area of probabilistic graphical models such as decision graphs, learning from data and inference. It presents a survey of the state of the art of specific topics of recent interest of Bayesian Networks, including approximate propagation, abductive inferences, decision graphs, and applications of influence. In addition, Advances in Bayesian Networks presents a careful selection of applications of probabilistic graphical models to various fields such as speech recognition, meteorology or information retrieval.

This item is Non-Returnable

Details

  • ISBN-13: 9783540208761
  • ISBN-10: 3540208763
  • Publisher: Springer
  • Publish Date: February 2004
  • Dimensions: 9.21 x 6.14 x 0.81 inches
  • Shipping Weight: 1.45 pounds
  • Page Count: 328

Related Categories

You May Also Like...

    1

BAM Customer Reviews