找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis; Uffe B. Kj?rulff,Anders L. Madsen Book 2013Latest edition

[復(fù)制鏈接]
查看: 20515|回復(fù): 45
樓主
發(fā)表于 2025-3-21 17:33:48 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis
影響因子2023Uffe B. Kj?rulff,Anders L. Madsen
視頻videohttp://file.papertrans.cn/182/181866/181866.mp4
發(fā)行地址Comprehensive introduction to understand, construct, and analyze probabilistic networks.Second Edition features six new sections covering such topics as structure learning and parameter tuning.New app
學(xué)科分類Information Science and Statistics
圖書封面Titlebook: Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis;  Uffe B. Kj?rulff,Anders L. Madsen Book 2013Latest edition
影響因子.Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis, Second Edition,.?provides a comprehensive guide for practitioners who wish to understand, construct, and analyze intelligent systems for decision support based on probabilistic networks. This new edition contains six new sections, in addition to fully-updated examples, tables, figures, and a revised appendix.? Intended primarily for practitioners, this book does not require sophisticated mathematical skills or deep understanding of the underlying theory and methods nor does it discuss alternative technologies for reasoning under uncertainty. The theory and methods presented are illustrated through more than 140 examples, and exercises are included for the reader to check his or her level of understanding. The techniques and methods presented for knowledge elicitation, model construction and verification, modeling techniques and tricks, learning models from data, and analyses of models have all been developed and refined on the basis of numerous courses that the authors have held for practitioners worldwide. .
Pindex Book 2013Latest edition
The information of publication is updating

書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis影響因子(影響力)




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis影響因子(影響力)學(xué)科排名




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis網(wǎng)絡(luò)公開度




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis被引頻次




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis被引頻次學(xué)科排名




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis年度引用




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis年度引用學(xué)科排名




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis讀者反饋




書目名稱Bayesian Networks and Influence Diagrams: A Guide to Construction and Analysis讀者反饋學(xué)科排名




單選投票, 共有 0 人參與投票
 

0票 0%

Perfect with Aesthetics

 

0票 0%

Better Implies Difficulty

 

0票 0%

Good and Satisfactory

 

0票 0%

Adverse Performance

 

0票 0%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 20:42:47 | 只看該作者
Networks of a graph and the interactions (direct dependences) as directed edges (links or arcs) between the vertices. Any pair of unconnected vertices of such a graph indicates (conditional) independence between the variables represented by these vertices under particular circumstances that can easily be re
板凳
發(fā)表于 2025-3-22 02:01:38 | 只看該作者
Probabilitiesrsive factorization of a joint probability distribution into a product of lower-dimensional conditional probability distributions. First, any joint probability distribution can be decomposed (or factorized) into a product of conditional distributions of different dimensionality, where the dimensiona
地板
發(fā)表于 2025-3-22 07:41:52 | 只看該作者
5#
發(fā)表于 2025-3-22 11:02:51 | 只看該作者
6#
發(fā)表于 2025-3-22 13:55:16 | 只看該作者
Eliciting the Model]. The structure of a probabilistic network is often referred to as the qualitative part of the network, whereas the parameters are often referred to as its quantitative part. As the parameters of a model are determined by its structure, the model elicitation process always proceeds in two consecuti
7#
發(fā)表于 2025-3-22 20:21:56 | 只看該作者
8#
發(fā)表于 2025-3-22 23:33:18 | 只看該作者
Data-Driven Modelingases and expert knowledge consists of two main steps. The first step is to induce the structure of the model, that is, the DAG, while the second step is to estimate the parameters of the model as defined by the structure. In this chapter we consider only discrete Bayesian networks. Thus, the task of
9#
發(fā)表于 2025-3-23 01:57:55 | 只看該作者
10#
發(fā)表于 2025-3-23 06:52:30 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-12 04:44
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
科尔| 南通市| 三河市| 义乌市| 北海市| 登封市| 玛纳斯县| 台北县| 文昌市| 美姑县| 资中县| 阿城市| 巧家县| 文水县| 徐水县| 靖州| 赤城县| 托克逊县| 陇川县| 滨州市| 临汾市| 玉树县| 凤台县| 景泰县| 渭南市| 昌邑市| 卓尼县| 车致| 桃源县| 天津市| 扎鲁特旗| 枣庄市| 庄浪县| 景泰县| 明星| 栾川县| 廉江市| 内江市| 资源县| 易门县| 鹤庆县|