Handbook of Cluster Analysis, Hennig, Christian

Название: Handbook of Cluster Analysis
ISBN: 1466551887 ISBN-13(EAN): 9781466551886
Издательство: Taylor&Francis
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Цена: 224570.00 T
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Описание:

Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active, distinguished researchers in this area, the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools.

The book is organized according to the traditional core approaches to cluster analysis, from the origins to recent developments. After an overview of approaches and a quick journey through the history of cluster analysis, the book focuses on the four major approaches to cluster analysis. These approaches include methods for optimizing an objective function that describes how well data is grouped around centroids, dissimilarity-based methods, mixture models and partitioning models, and clustering methods inspired by nonparametric density estimation. The book also describes additional approaches to cluster analysis, including constrained and semi-supervised clustering, and explores other relevant issues, such as evaluating the quality of a cluster.

This handbook is accessible to readers from various disciplines, reflecting the interdisciplinary nature of cluster analysis. For those already experienced with cluster analysis, the book offers a broad and structured overview. For newcomers to the field, it presents an introduction to key issues. For researchers who are temporarily or marginally involved with cluster analysis problems, the book gives enough algorithmic and practical details to facilitate working knowledge of specific clustering areas.

Автор: Abonyi JГЎnos, Feil BalГЎzs
Название: Cluster Analysis for Data Mining and System Identification
ISBN: 3764379871 ISBN-13(EAN): 9783764379872
Издательство: Springer
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Цена: 93130.00 T
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Описание: This book presents new approaches to data mining and system identification. Algorithmsthat can be used for the clustering of data have been overviewed. New techniques andtools are presented for the clustering, classification, regression and visualization ofcomplex datasets. Special attention is given to the analysis of historical process data,tailored algorithms are presented for the data driven modeling of dynamical systems,determining the model order of nonlinear input-output black box models, and thesegmentation of multivariate time-series. The main methods and techniques areillustrated through several simulated and real-world applications from data mining andprocess engineering practice.The books is aimed primarily at practitioners, researches, and professionals in statistics,data mining, business intelligence, and systems engineering, but it is also accessible tograduate and undergraduate students in applied mathematics, computer science, electricaland process engineering. Familiarity with the basics of system identification and fuzzysystems is helpful but not required.

Автор: Mirkin, Boris
Название: Clustering for Data Mining
ISBN: 1584885343 ISBN-13(EAN): 9781584885344
Издательство: Taylor&Francis
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Цена: 61240.00 T
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Описание: Presents a theory that not only closes gaps in K-Means and Ward methods, but also extends them into areas of interest, such as clustering mixed scale data and incomplete clustering. This work suggests methods for both cluster finding and cluster description, and includes nearly 60 computational examples covering the various stages of clustering.

Автор: Maharaj
Название: Time Series Clustering And Classifi
ISBN: 1498773214 ISBN-13(EAN): 9781498773218
Издательство: Taylor&Francis
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Цена: 168430.00 T
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Описание: This book includes relevant developments on observation-based, feature-based and model-based traditional and fuzzy clustering methods, feature-based and model-based classification methods, and machine learning methods. It presents a broad and self-contained overview of techniques for both researchers and students.

Автор: Toshiro Tango
Название: Statistical Methods for Disease Clustering
ISBN: 1461425565 ISBN-13(EAN): 9781461425564
Издательство: Springer
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Цена: 121110.00 T
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Описание: This book offers a modern perspective on statistical methods for detecting disease clustering. It offers analysis and illustration of methods for a variety of real data sets, and will provide an invaluable resource for a wide ranging of audience.

Автор: Wicher Bergsma; Marcel A. Croon; Jacques A. Hagena
Название: Marginal Models
ISBN: 1441918736 ISBN-13(EAN): 9781441918734
Издательство: Springer
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Цена: 121110.00 T
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Описание: Marginal models are often the best way of answering research questions involving dependent observations. This comprehensive overview of the basic principles of marginal modeling offers a wide range of possible applications through many real world examples.

Автор: Ritter, Gunter
Название: Robust Cluster Analysis and Variable Selection
ISBN: 1439857962 ISBN-13(EAN): 9781439857960
Издательство: Taylor&Francis
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Цена: 163330.00 T
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Автор: A.R. Rao; V. V. Srinivas
Название: Regionalization of Watersheds
ISBN: 9048177375 ISBN-13(EAN): 9789048177370
Издательство: Springer
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Цена: 144410.00 T
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Описание: Clustering techniques are used to identify groups of watersheds which have similar flood characteristics. It provides a detailed account of several recently developed clustering techniques, including those based on fuzzy set theory.

Автор: Palestini Claudio
Название: Advanced Technologies for Security Applications: Proceedings of the NATO Science for Peace and Security `cluster Workshop on Advanced Technologies`, 1
ISBN: 9402420207 ISBN-13(EAN): 9789402420203
Издательство: Springer
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Цена: 139750.00 T
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Описание: On 17-18 September 2019, the SPS Programme gathered at the KU Leuven University a wide number of researchers from a selection of on-going and recently closed SPS projects in the field of security-related advanced technologies for a "Cluster Workshop on Advanced Technologies".

Автор: Hayes, Richard J. (london School Of Hygiene & Tropical Medicine, Uk) Moulton, Lawrence H. (johns Hopkins Bloomberg School Of Public Health, Baltimore,
Название: Cluster randomised trials
ISBN: 1032339586 ISBN-13(EAN): 9781032339580
Издательство: Taylor&Francis
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Цена: 50010.00 T
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Описание: Cluster Randomised Trials, Second Edition explores the advantages of cluster randomisation, with special attention given to evaluating the effects of interventions against infectious diseases. Avoiding unnecessary mathematical detail, it covers basic concepts underlying the use of cluster randomisation.

Автор: Palestini Claudio
Название: Advanced Technologies for Security Applications: Proceedings of the NATO Science for Peace and Security `cluster Workshop on Advanced Technologies`, 1
ISBN: 9402420231 ISBN-13(EAN): 9789402420234
Издательство: Springer
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Цена: 139750.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: On 17-18 September 2019, the SPS Programme gathered at the KU Leuven University a wide number of researchers from a selection of on-going and recently closed SPS projects in the field of security-related advanced technologies for a "Cluster Workshop on Advanced Technologies".

Автор: Ngianga-Bakwin Kandala
Название: Statistical Modelling of Complex Correlated and Clustered Data Household Surveys in Africa
ISBN: 1536159816 ISBN-13(EAN): 9781536159813
Издательство: Nova Science
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Цена: 215410.00 T
Наличие на складе: Невозможна поставка.
Описание: In order to assist a hospital in managing its resources and patients, modelling the length of stay is highly important. Recent health scholarship and practice has largely remained empirical, dwelling on primary data. This is critically important, first, because health planners generally rely on data to establish trends and patterns of disease burden at national or regional level. Secondly, epidemiologists depend on data to investigate possible risk factors of the disease. Yet the use of routine or secondary data has, in recent years, proved increasingly significant in such endeavours. Various units within the health systems collected such data primarily as part of the process for surveillance, monitoring and evaluation. Such data is sometimes periodically supplemented by population-based sample survey datasets. Thirdly, coupled with statistical tools, public health professionals are able to analyze health data and breathe life into what may turn out to be meaningless data. The main focus of this book is to present and showcase advanced modelling of routine or secondary survey data. Studies demonstrate that statistical literacy and knowledge are needed to understand health research outputs. The advent of user-friendly statistical packages combined with computing power and widespread availability of public health data resulted in more reported epidemiological studies in literature. However, analysis of secondary data, has some unique challenges. These are most widely reported health literature, so far has failed to recognize resulting in inappropriate analysis, and erroneous conclusions. This book presents the application of advanced statistical techniques to real examples emanating from routine or secondary survey data. These are essentially datasets in which the two editors have been involved, demonstrating how to tackle these challenges. Some of these challenges are: the complex sampling design of the surveys, the hierarchical nature of the data, the dependence of data at the sampled cluster and missing data among many more challenges. Using data from the Health Management Information System (HMIS), and Demographic and Health Survey (DHS), we provide various approaches and techniques of dealing with data complexity, how to handle correlated or clustered data. Each chapter presents an example code, which can be used to analyze similar data in R, Stata or SPSS. To make the book more concise, we have provided the codes on the books website. The book considers four main topics in the field of health sciences research: (i) structural equation modeling; (ii) spatial and spatio-temporal modeling; (iii) correlated or clustered copula modeling; and (iv) survival analysis. The book has potential to impact methodologists, including students undertaking Masters or Doctoral level programmes as well as other researchers seeking some related reference on quantitative analysis in public health or health sciences or other areas where data of similar nature would be applicable. Further the book can be a resource to public health professionals interested in quantitative approaches to answer questions of epidemiological nature. Each chapter starts with a motivating background, review of statistical methods, analysis and results, ending discussion and possible recommendations.