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About Fuzzy Cluster Analysis: Methods for Classification, Data Analysis and Image Recognition
Представляет своевременное и важное введение в нечеткий кластерный анализ, его методы и области использования. Систематически описывает различные техники нечеткой кластеризации так что читатель может выбарть метод, наиболее подходящий для решения его задачи. Присутствует хороший и очень полный обзор литературы по предмету исследования, распознаванию изображений, классификации покрытий, анализу данных и выводу правил. Примеры достаточно иллюстративны и доставляют. результаты апробированы.Это наиболее подробная книга по нечеткой кластеризации, вследствие чего рекомендуется ученым-компьютерщикам, математикам, инженерам -- всем, кто связан с анализом данных, обработкой изображений. Будет также полезна студентам, которые подвизаются в области вычислительных наук.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
Detailed Information
| Author: | Frank Höppner, Rudolf Kruse, Frank Klawonn, Thomas Runkler |
|---|---|
| Publication Year: | 1999 |
| Pages: | 288 |
| Language: | English |
| File Size: | 200.066 |
| Format: | |
| Price: | FREE |
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