Random Graphs for Statistical Pattern Recognition
暫譯: 隨機圖在統計模式識別中的應用

David J. Marchette

  • 出版商: Wiley
  • 出版日期: 2004-02-23
  • 售價: $6,030
  • 貴賓價: 9.5$5,729
  • 語言: 英文
  • 頁數: 264
  • 裝訂: Hardcover
  • ISBN: 0471221767
  • ISBN-13: 9780471221760
  • 海外代購書籍(需單獨結帳)

買這商品的人也買了...

相關主題

商品描述

Description:

A timely convergence of two widely used disciplines

Random Graphs for Statistical Pattern Recognition is the first book to address the topic of random graphs as it applies to statistical pattern recognition. Both topics are of vital interest to researchers in various mathematical and statistical fields and have never before been treated together in one book. The use of data random graphs in pattern recognition in clustering and classification is discussed, and the applications for both disciplines are enhanced with new tools for the statistical pattern recognition community. New and interesting applications for random graph users are also introduced.

This important addition to statistical literature features:

  • Information that previously has been available only through scattered journal articles
  • Practical tools and techniques for a wide range of real-world applications
  • New perspectives on the relationship between pattern recognition and computational geometry
  • Numerous experimental problems to encourage practical applications

With its comprehensive coverage of two timely fields, enhanced with many references and real-world examples, Random Graphs for Statistical Pattern Recognition is a valuable resource for industry professionals and students alike.

 

Table of Contents:

Preface.

Acknowledgments.

1. Preliminaries.

1.1 Graphs and Digraphs.

1.2 Statistical Pattern Recognition.

1.3 Statistical Issues.

1.4 Applications.

1.5 Further Reading.

2. Computational Geometry.

2.1 Introduction.

2.2 Voronoi Cells and Delaunay Triangularization.

2.3 Alpha Hulls.

2.4 Minimum Spanning Trees.

2.5 Further Reading.

3. Neighborhood Graphs.

3.1 Introduction.

3.2 Nearest-Neighbor Graphs.

3.3 k-Nearest Neighbor Graphs.

3.4 Relative Neighborhood Graphs.

3.5 Gabriel Graphs.

3.6 Application: Nearest Neighbor Prototypes.

3.7 Sphere of Influence Graphs.

3.8 Other Relatives.

3.9 Asymptotics.

3.10 Further Reading.

4. Class Cover Catch Digraphs.

4.1 Catch Digraphs.

4.2 Class Covers.

4.3 Dominating Sets.

4.4 Distributional Results for Cn,m-graphs.

4.5 Characterizations.

4.6 Scale Dimension.

4.7 (α,β) Graphs

4.8 CCCD Classification.

4.9 Homogeneous CCCDs.

4.10 Vector Quantization.

4.11 Random Walk Version.

4.12 Further Reading.

5. Cluster Catch Digraphs.

5.1 Basic Definitions.

5.2 Dominating Sets.

5.3 Connected Components.

5.4 Variable Metric Clustering.

6. Computational Methods.

6.1 Introduction.

6.2 Kd-Trees.

6.3 Class Cover Catch Digraphs.

6.4 Cluster Catch Digraphs.

6.5 Voroni Regions and Delaunay Triangularizations.

6.6 Further Reading.

References.

Author Index.

Subject Index.

 

 

商品描述(中文翻譯)

**描述:**
隨著隨機圖與統計模式識別兩個廣泛使用的學科的及時融合,《隨機圖與統計模式識別》是第一本探討隨機圖在統計模式識別中應用的書籍。這兩個主題對於各種數學和統計領域的研究人員來說都至關重要,且從未在一本書中同時處理過。書中討論了在聚類和分類中使用數據隨機圖的情況,並為統計模式識別社群提供了新的工具來增強這兩個學科的應用。書中還介紹了隨機圖使用者的新穎且有趣的應用。

這本對統計文獻的重要補充具有以下特點:
- 之前僅能通過零散的期刊文章獲得的信息
- 適用於各種現實世界應用的實用工具和技術
- 對模式識別與計算幾何之間關係的新視角
- 許多實驗問題以鼓勵實際應用

《隨機圖與統計模式識別》全面涵蓋了這兩個及時的領域,並增添了許多參考資料和現實世界的例子,是業界專業人士和學生的寶貴資源。

**目錄:**
前言
致謝
1. 基礎知識
1.1 圖與有向圖
1.2 統計模式識別
1.3 統計問題
1.4 應用
1.5 進一步閱讀
2. 計算幾何
2.1 介紹
2.2 Voronoi 單元與 Delaunay 三角化
2.3 Alpha Hulls
2.4 最小生成樹
2.5 進一步閱讀
3. 鄰域圖
3.1 介紹
3.2 最近鄰圖
3.3 k-最近鄰圖
3.4 相對鄰域圖
3.5 Gabriel 圖
3.6 應用:最近鄰原型
3.7 影響範圍圖
3.8 其他相關圖
3.9 漸近性
3.10 進一步閱讀
4. 類別覆蓋捕捉有向圖
4.1 捕捉有向圖
4.2 類別覆蓋
4.3 主導集
4.4 Cn,m-圖的分佈結果
4.5 特徵化
4.6 標度維度
4.7 (α,β) 圖
4.8 CCCD 分類
4.9 同質 CCCD
4.10 向量量化
4.11 隨機漫步版本
4.12 進一步閱讀
5. 聚類捕捉有向圖
5.1 基本定義
5.2 主導集
5.3 連通分量
5.4 可變度量聚類
6. 計算方法
6.1 介紹
6.2 Kd-Trees
6.3 類別覆蓋捕捉有向圖
6.4 聚類捕捉有向圖
6.5 Voronoi 區域與 Delaunay 三角化
6.6 進一步閱讀
參考文獻
作者索引
主題索引