Partitional Clustering Algorithms by M. Emre CelebiPartitional Clustering Algorithms by M. Emre Celebi

Partitional Clustering Algorithms

byM. Emre Celebi

Hardcover | November 20, 2014

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This book focuses on partitional clustering algorithms, which are commonly used in engineering and computer scientific applications. The goal of this volume is to summarize the state-of-the-art in partitional clustering. The book includes such topics as center-based clustering, competitive learning clustering and density-based clustering. Each chapter is contributed by a leading expert in the field.
Dr. Emre Celebi is an Associate Professor with the Department of Computer Science, at Louisiana State University in Shreveport.
Title:Partitional Clustering AlgorithmsFormat:HardcoverDimensions:415 pagesPublished:November 20, 2014Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319092588

ISBN - 13:9783319092584

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Table of Contents

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.

Editorial Reviews

"The content of the book is really outstanding in terms of the clarity of the discourse and the variety of well-selected examples. . The book brings substantial contributions to the field of partitional clustering from both the theoretical and practical points of view, with the concepts and algorithms presented in a clear and accessible way. It addresses a wide range of readers, including scientists, students, and researchers." (L. State, Computing Reviews, April, 2015)