Clustering

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Algorithms For Clustering Data

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Author : Anil K. Jain
language : en
Publisher:
Release Date : 1988

Algorithms For Clustering Data written by Anil K. Jain and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Computers categories.

Constrained Clustering

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Author : Sugato Basu
language : en
Publisher: CRC Press
Release Date : 2008-08-18

Constrained Clustering written by Sugato Basu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-08-18 with Business & Economics categories.

This volume encompasses many new types of constraints and clustering methods as well as delivers thorough coverage of the capabilities and limitations of constrained clustering. With contributions from industrial researchers and leading academic experts who pioneered the field, it provides a well-balanced combination of theoretical advances, key algorithmic development, and novel applications. The book presents various types of constraints for clustering and describes useful variations of the standard problem of clustering under constraints. It also demonstrates the application of clustering with constraints to relational, bibliographic, and video data.

Data Clustering

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Author : Charu C. Aggarwal
language : en
Publisher: CRC Press
Release Date : 2013-08-21

Data Clustering written by Charu C. Aggarwal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-21 with Business & Economics categories.

Research on the problem of clustering tends to be fragmented across the pattern recognition, database, data mining, and machine learning communities. Addressing this problem in a unified way, Data Clustering: Algorithms and Applications provides complete coverage of the entire area of clustering, from basic methods to more refined and complex data clustering approaches. It pays special attention to recent issues in graphs, social networks, and other domains. The book focuses on three primary aspects of data clustering: Methods, describing key techniques commonly used for clustering, such as feature selection, agglomerative clustering, partitional clustering, density-based clustering, probabilistic clustering, grid-based clustering, spectral clustering, and nonnegative matrix factorization Domains, covering methods used for different domains of data, such as categorical data, text data, multimedia data, graph data, biological data, stream data, uncertain data, time series clustering, high-dimensional clustering, and big data Variations and Insights, discussing important variations of the clustering process, such as semisupervised clustering, interactive clustering, multiview clustering, cluster ensembles, and cluster validation In this book, top researchers from around the world explore the characteristics of clustering problems in a variety of application areas. They also explain how to glean detailed insight from the clustering process—including how to verify the quality of the underlying clusters—through supervision, human intervention, or the automated generation of alternative clusters.

Cluster Analysis For Researchers

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Author : H. Charles Romesburg
language : en
Publisher: Lifetime Learning
Release Date : 1984

Cluster Analysis For Researchers written by H. Charles Romesburg and has been published by Lifetime Learning this book supported file pdf, txt, epub, kindle and other format this book has been release on 1984 with Mathematics categories.

Algorithms For Fuzzy Clustering

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Author : Sadaaki Miyamoto
language : en
Publisher: Springer
Release Date : 2008-04-10

Algorithms For Fuzzy Clustering written by Sadaaki Miyamoto and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-10 with Computers categories.

Recently many researchers are working on cluster analysis as a main tool for exploratory data analysis and data mining. A notable feature is that specialists in di?erent ?elds of sciences are considering the tool of data clustering to be useful. A major reason is that clustering algorithms and software are ?exible in thesensethatdi?erentmathematicalframeworksareemployedinthealgorithms and a user can select a suitable method according to his application. Moreover clusteringalgorithmshavedi?erentoutputsrangingfromtheolddendrogramsof agglomerativeclustering to more recent self-organizingmaps. Thus, a researcher or user can choose an appropriate output suited to his purpose,which is another ?exibility of the methods of clustering. An old and still most popular method is the K-means which use K cluster centers. A group of data is gathered around a cluster center and thus forms a cluster. The main subject of this book is the fuzzy c-means proposed by Dunn and Bezdek and their variations including recent studies. A main reasonwhy we concentrate on fuzzy c-means is that most methodology and application studies infuzzy clusteringusefuzzy c-means,andfuzzy c-meansshouldbe consideredto beamajortechniqueofclusteringingeneral,regardlesswhetheroneisinterested in fuzzy methods or not. Moreover recent advances in clustering techniques are rapid and we requirea new textbook that includes recent algorithms.We should also note that several books have recently been published but the contents do not include some methods studied herein.

Data Clustering

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Author :
language : en
Publisher: BoD – Books on Demand
Release Date : 2022-08-17

Data Clustering written by and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-17 with Computers categories.

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.

Clustering And Fuzzy Techniques

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Author : Hizir
language : en
Publisher: Tenea Verlag Ltd.
Release Date : 2003

Clustering And Fuzzy Techniques written by Hizir and has been published by Tenea Verlag Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.

Grouping Multidimensional Data

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Author : Jacob Kogan
language : en
Publisher: Taylor & Francis
Release Date : 2006-02-10

Grouping Multidimensional Data written by Jacob Kogan and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-02-10 with Computers categories.

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Cluster Analysis

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Author : Brian Everitt
language : en
Publisher:
Release Date : 1974

Cluster Analysis written by Brian Everitt and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974 with Cluster analysis categories.

A review of clustering techniques; A discussion of the problems of cluster analysis; An empirical investigation of some methods of cluster analysis; Using cluster analysis techniques in practice: some guide lines.

Data Science

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Author : Francesco Palumbo
language : en
Publisher: Springer
Release Date : 2017-07-04

Data Science written by Francesco Palumbo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-04 with Mathematics categories.

This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.