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ISBN: 3170013610 Year: 1980 Publisher: Stuttgart Kohlhammer
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ISBN: 9789811241192 Year: 2022 Publisher: Singapore World Scientific Publishing Co. Pte. Ltd.
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Year: 2019 Publisher: New York, New York : Association for Computing Machinery,
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ISBN: 0894644262 Year: 1990 Publisher: Malabar Krieger
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Article
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Belgium --- cluster analysis --- forests
ISBN: 0471988642 Year: 1999 Publisher: New York (N.Y.) : Wiley,
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Provides a timely and important introduction to fuzzy cluster analysis, its methods and areas of application, systematically describing different fuzzy clustering techniques so the user may choose methods appropriate for his problem. It provides a very thorough overview of the subject and covers classification, image recognition, data analysis and rule generation. The application examples are highly relevant and illustrative, and the use of the techniques are justified and well thought-out.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 measuresThis is one of the most comprehensive books on fuzzy clustering and will be welcomed by computer scientists, engineers and mathematicians in industry and research who are concerned with different methods, data analysis, pattern recognition or image processing. It will also give graduate students in computer science, mathematics or statistics a valuable overview.
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Year: 2022 Publisher: London : IntechOpen,
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In view of the considerable applications of data clustering techniques in various fields, such as engineering, artificial intelligence, machine learning, clinical medicine, biology, ecology, disease diagnosis, and business marketing, many data clustering algorithms and methods have been developed to deal with complicated data. These techniques include supervised learning methods and unsupervised learning methods such as density-based clustering, K-means clustering, and K-nearest neighbor clustering. This book reviews recently developed data clustering techniques and algorithms and discusses the development of data clustering, including measures of similarity or dissimilarity for data clustering, data clustering algorithms, assessment of clustering algorithms, and data clustering methods recently developed for insurance, psychology, pattern recognition, and survey data.
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ISBN: 9189416120 Year: 2005 Publisher: Boras Valfrid
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Year: 2022 Publisher: London : IntechOpen,
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In view of the considerable applications of data clustering techniques in various fields, such as engineering, artificial intelligence, machine learning, clinical medicine, biology, ecology, disease diagnosis, and business marketing, many data clustering algorithms and methods have been developed to deal with complicated data. These techniques include supervised learning methods and unsupervised learning methods such as density-based clustering, K-means clustering, and K-nearest neighbor clustering. This book reviews recently developed data clustering techniques and algorithms and discusses the development of data clustering, including measures of similarity or dissimilarity for data clustering, data clustering algorithms, assessment of clustering algorithms, and data clustering methods recently developed for insurance, psychology, pattern recognition, and survey data.
Book
ISBN: 0894643584 Year: 1989 Publisher: Malabar Krieger
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