Partitional Clustering Algorithms (Record no. 57862)

000 -LEADER
fixed length control field 03513nam a22004575i 4500
001 - CONTROL NUMBER
control field 978-3-319-09259-1
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200421112229.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 141107s2015 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9783319092591
-- 978-3-319-09259-1
082 04 - CLASSIFICATION NUMBER
Call Number 621.382
245 10 - TITLE STATEMENT
Title Partitional Clustering Algorithms
300 ## - PHYSICAL DESCRIPTION
Number of Pages X, 415 p. 78 illus., 45 illus. in color.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Recent developments in model-based clustering with applications -- Accelerating Lloyd's algorithm for k-means clustering -- Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm -- Nonsmooth optimization based algorithms in cluster analysis -- Fuzzy Clustering Algorithms and Validity Indices for Distributed Data -- Density Based Clustering: Alternatives to DBSCAN -- Nonnegative matrix factorization for interactive topic modeling and document clustering -- Overview of overlapping partitional clustering methods -- On Semi-Supervised Clustering -- Consensus of Clusterings based on High-order Dissimilarities -- Hubness-Based Clustering of High-Dimensional Data -- Clustering for Monitoring Distributed Data Streams.
520 ## - SUMMARY, ETC.
Summary, etc This book summarizes the state-of-the-art in partitional clustering. Clustering, the unsupervised classification of patterns into groups, is one of the most important tasks in exploratory data analysis. Primary goals of clustering include gaining insight into, classifying, and compressing data. Clustering has a long and rich history that spans a variety of scientific disciplines including anthropology, biology, medicine, psychology, statistics, mathematics, engineering, and computer science. As a result, numerous clustering algorithms have been proposed since the early 1950s. Among these algorithms, partitional (nonhierarchical) ones have found many applications, especially in engineering and computer science. This book provides coverage of consensus clustering, constrained clustering, large scale and/or high dimensional clustering, cluster validity, cluster visualization, and applications of clustering. Examines clustering as it applies to large and/or high-dimensional data sets commonly encountered in realistic applications; Discusses algorithms specifically designed for partitional clustering; Covers center-based, competitive learning, density-based, fuzzy, graph-based, grid-based, metaheuristic, and model-based approaches.
700 1# - AUTHOR 2
Author 2 Celebi, M. Emre.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier http://dx.doi.org/10.1007/978-3-319-09259-1
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
264 #1 -
-- Cham :
-- Springer International Publishing :
-- Imprint: Springer,
-- 2015.
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-- rdacontent
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-- computer
-- c
-- rdamedia
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-- online resource
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-- text file
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650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Computers.
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Electrical engineering.
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Engineering.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Communications Engineering, Networks.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Information Systems and Communication Service.
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Signal, Image and Speech Processing.
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-- ZDB-2-ENG

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