Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Rec
暫譯: 模糊聚類分析:分類、數據分析與影像重建的方法

Frank Höppner, Frank Klawonn, Rudolf Kruse, Thomas Runkler

  • 出版商: Wiley
  • 出版日期: 1999-07-09
  • 售價: $855
  • 語言: 英文
  • 頁數: 300
  • 裝訂: Hardcover
  • ISBN: 0471988642
  • ISBN-13: 9780471988649
  • 相關分類: Data Science
  • 已絕版

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商品描述

Fuzzy Cluster Analysis presents advanced and powerful fuzzy clustering techniques. This thorough and self-contained introduction to fuzzy clustering methods and applications covers classification, image recognition, data analysis and rule generation. Combining theoretical and practical perspectives, each method is analysed in detail and fully illustrated with examples. Features include:
  • Sections on inducing fuzzy if-then rules by fuzzy clustering and non-alternating optimization fuzzy clustering algorithms
  • Discussion of solid fuzzy clustering techniques like the fuzzy c-means, the Gustafson-Kessel and the Gath-and-Geva algorithm for classification problems
  • Focus on linear and shell clustering techniques used for detecting contours in image analysis
  • Accompanying software and data sets pertaining to the examples presented, enabling the reader to learn through experimentation
  • Examination of the difficulties involved in evaluating the results of fuzzy cluster analysis and of determining the number of clusters with analysis of global and local validity measures
  • Description of different fuzzy clustering techniques allowing the user to select the method most appropriate to a particular problem
Computer scientists, engineers and mathematicians in industry and research who are concerned with fuzzy clustering methods, data analysis, pattern recognition or image processing will find this a timely and accessible resource. Graduate students in computer science, mathematics or statistics will value this comprehensive overview of the applications of fuzzy methods. Download accompanying program and data sets from our website

商品描述(中文翻譯)

模糊聚類分析介紹了先進且強大的模糊聚類技術。這本全面且自成體系的模糊聚類方法與應用的入門書涵蓋了分類、圖像識別、數據分析和規則生成。結合理論與實踐的觀點,每種方法都進行了詳細分析,並配有完整的示例說明。主要特點包括:

- 有關通過模糊聚類和非交替優化模糊聚類算法引導模糊如果-則規則的章節
- 討論穩健的模糊聚類技術,如模糊 c-均值、Gustafson-Kessel 和 Gath-and-Geva 算法在分類問題中的應用
- 專注於用於檢測圖像分析中輪廓的線性和外殼聚類技術
- 附帶與所呈現示例相關的軟體和數據集,使讀者能夠通過實驗學習
- 檢視評估模糊聚類分析結果的困難,以及確定聚類數量的全球和局部有效性度量分析
- 描述不同的模糊聚類技術,使用者可以選擇最適合特定問題的方法

從事模糊聚類方法、數據分析、模式識別或圖像處理的計算機科學家、工程師和數學家將會發現這是一本及時且易於接觸的資源。計算機科學、數學或統計學的研究生將會重視這本對模糊方法應用的全面概述。請從我們的網站下載附帶的程式和數據集。

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