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Cluster Analysis
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Mark S Aldenderfer, Roger K Blashfield
Although clustering -- the classifying of objects into meaningful sets -- is an important procedure, cluster analysis as a multivariate statistical procedure is poorly understood. This volume is an introduction to cluster analysis for professionals, as well as for advanced undergraduate and graduate students with little or no background in the ...
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Cluster and Classification Techniques for the Biosciences
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Alan H Fielding
Recent advances in experimental methods have resulted in the generation of enormous volumes of data across the life sciences. Hence clustering and classification techniques that were once predominantly the domain of ecologists are now being used more widely. This book provides an overview of these important data analysis methods, from long ...
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Survey of Text Mining: Clustering, Classification, and Retrieval
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Michael W Berry (Editor)
Extracting content from text continues to be an important research problem for information processing and management. Approaches to capture the semantics of text-based document collections may be based on Bayesian models, probability theory, vector space models, statistical models, or even graph theory. As the volume of digitized textual media ...
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Cluster Analysis
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Brian Everitt
This practical text has been reworked to provide an account of the subject of cluster analysis - the generic name for a wide variety of procedures involved with identifying groups within data. By organizing multivariate data into such subgroups clustering may help the investigator discover the characteristics of any structure or pattern present. ...
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Topics in Modelling of Clustered Data
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Marc Aerts (Editor), Geert Molenberghs (Editor), Louise M Ryan (Editor)
Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Compiled from the contributions of leading specialists in the field, Topics in Modelling of Clustered Data describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, ...
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Finding Groups in Data: An Introduction to Cluster Analysis
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Leonard Kaufman, Peter J Rousseeuw
An introduction to the practical application of cluster analysis, Finding Groups in Data presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. The text discusses the main approaches to clustering and provides guidance in choosing between ...
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Cluster Randomised Trials
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Richard J Hayes, Dsc, Lawrence H Moulton
There is an increasing need for new health interventions to be rigorously evaluated through randomized controlled trials, which have become the gold standard for intervention studies. In addition, there is increasing acceptance of cluster randomized trials (CRTs) as the most appropriate choice of study design. "Cluster Randomised Trials" covers ...
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Clustering and Information Retrieval
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by
Weili Wu, Hui Xiong, Shashi Shekhar (Editor)
This volume contains recent developments in clustering and information retrieval, including clustering algorithms, evaluation methodologies, and architectures for information retrieval. It provides a survey of the state-of-the-art research in clustering and information retrieval. Audience: This volume is suitable for professionals and researchers ...
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Clustering and Classification
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by
Phipps Arabie
At a moderately advanced level, this book seeks to cover the areas of clustering and related methods of data analysis where major advances are being made. Topics include: hierarchical clustering; variable selection and weighting; additive trees and other network models; relevance of neural network models to clustering; the role of computational ...
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Cluster dissection and analysis theory, FORTRAN programs, examples
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Späth
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Machine Learning and Data Mining in Pattern Recognition: 5th International Conference, MLDM 2007, Leipzig, Germany, July 18-20, 2007, Proceedings
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by
Petra Perner
This book constitutes the refereed proceedings of the 5th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2007, held in Leipzig, Germany, in July 2007. The 66 revised full papers presented together with one invited talk were carefully reviewed and selected from 258 submissions. The papers are organized in ...
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Cluster analysis algorithms for data reduction and classification of objects
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by
Helmuth Späth
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Data Science, Classification, and Related Methods
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by
International Federation Of Classification Societies, Hans H Bock (Editor), Yutaka Tanaka (Editor)
This is the proceedings of the Fifth Conference of the International Federation of Classification Societies held in Kobe, Japan, on March 27-30, 1996: The astounding increase in computer usage over the past decade and the ever-increasing scope of global communication networks have ushered in the information age; however, human intelligence is ...
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Gibbs random fields cluster expansions
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Malyshev, Minlos
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Three Way Scaling: A Guide to Multidimensional Scaling and Clustering
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Phipps Arabie, J Douglas Carroll, John L Sullivan (Introduction by)
Three Way Scaling assumes a working knowledge of multidimensional scaling and Matrix Algebra, which are both introduced in earlier volumes of this series. Arabie, Carroll and DeSarbo begin their discussion with an example of the use of the INDSCAL model, they explain the model and give a second extended example. The authors then present a detailed ...
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The Interpretation of Analytical Chemical Data by the Use of Cluster Analysis
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Small Business Clustering Technologies: Applications in Marketing, Management, It and Economics
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by
Robert C MacGregor
"Small Business Clustering Technology: Applications in Marketing, Management, Finance and IT" examines the development and role of small business clusters from a variety of disciplines - economics, marketing, management, and information systems. Unlike many issues that are hampered by ideological problems between disciplines, this book proves that ...
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Fuzzy sets in information retrieval and cluster analysis
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Miyamoto
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Foundations of Quantization for Probability Distributions
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Siegfried Graf, Harald Luschgy, Bala Natarajan
Due to the rapidly increasing need for methods of data compression, quantization has become a flourishing field in signal and image processing and information theory. The same techniques are also used in statistics (cluster analysis), pattern recognition, and operations research (optimal location of service centers). The book gives the first ...
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Computer-Assisted Reasoning in Cluster Analysis
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by
Abraham Kandel, Eric Backer
This book bridges the gap between daily practice of cluster analysis and computer-assisted (knowledge-based) diagnostic support in cluster analysis. It incorporates hands-on experience through the EDAPLUS software package that goes with the book. Coverage includes a detailed explanation of the concept of fuzzy sets and fuzzy logic in cluster ...
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Cluster Analysis for Applications
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by
Michael R Anderberg
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Fuzz Models and Algorithms for Pattern Recogniton and Image Prcessing
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James Keller, Raghu Krisnapuram, James C Bezdek
Fuzzy Models and Algorithms for Pattern Recognition and Image Processing presents a comprehensive introduction of the use of fuzzy models in pattern recognition and selected topics in image processing and computer vision. Unique to this volume in the Kluwer Handbooks of Fuzzy Sets Series is the fact that this book was written in its entirety by ...
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Classification and Clustering: Proceedings of an Advanced Seminar Conducted by the Mathematics Research Center, the University of Wisconsin--Madison, May 3-5, 1976
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John Van Ryzin
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Clustering for Data Mining: A Data Recovery Approach
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by
Boris Mirkin
Often considered more as an art than a science, the field of clustering has been dominated by learning through examples and by techniques chosen almost through trial-and-error. Even the most popular clustering methods - K-Means for partitioning the data set and Ward's method for hierarchical clustering - have lacked the theoretical attention that ...
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Constrained Clustering: Advances in Algorithms, Theory, and Applications
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Sugato Basu (Editor), Ian Davidson (Editor), Kiri Wagstaff (Editor)
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. It presents various types of constraints for clustering, describes useful variations of the standard problem of clustering under constraints, and applies clustering with ...
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