Clustering And Classification PDF Download
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| Author | : Phipps Arabie |
| Publisher | : World Scientific |
| Total Pages | : 508 |
| Release | : 1996 |
| Genre | : Mathematics |
| ISBN | : 9789810212872 |
Download Clustering and Classification Book in PDF, ePub and Kindle
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 complexity in cluster analysis, latent class approaches to cluster analysis, theory and method with applications of a hierarchical classes model in psychology and psychopathology, combinatorial data analysis, clusterwise aggregation of relations, review of the Japanese-language results on clustering, review of the Russian-language results on clustering and multidimensional scaling, practical advances, and significance tests.
| Author | : Charles Bouveyron |
| Publisher | : Cambridge University Press |
| Total Pages | : 447 |
| Release | : 2019-07-25 |
| Genre | : Mathematics |
| ISBN | : 1108640591 |
Download Model-Based Clustering and Classification for Data Science Book in PDF, ePub and Kindle
Cluster analysis finds groups in data automatically. Most methods have been heuristic and leave open such central questions as: how many clusters are there? Which method should I use? How should I handle outliers? Classification assigns new observations to groups given previously classified observations, and also has open questions about parameter tuning, robustness and uncertainty assessment. This book frames cluster analysis and classification in terms of statistical models, thus yielding principled estimation, testing and prediction methods, and sound answers to the central questions. It builds the basic ideas in an accessible but rigorous way, with extensive data examples and R code; describes modern approaches to high-dimensional data and networks; and explains such recent advances as Bayesian regularization, non-Gaussian model-based clustering, cluster merging, variable selection, semi-supervised and robust classification, clustering of functional data, text and images, and co-clustering. Written for advanced undergraduates in data science, as well as researchers and practitioners, it assumes basic knowledge of multivariate calculus, linear algebra, probability and statistics.
| Author | : Krzystof Jajuga |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 468 |
| Release | : 2012-12-06 |
| Genre | : Computers |
| ISBN | : 3642561810 |
Download Classification, Clustering, and Data Analysis Book in PDF, ePub and Kindle
The book presents a long list of useful methods for classification, clustering and data analysis. By combining theoretical aspects with practical problems, it is designed for researchers as well as for applied statisticians and will support the fast transfer of new methodological advances to a wide range of applications.
| Author | : Boris Mirkin |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 439 |
| Release | : 2013-12-01 |
| Genre | : Mathematics |
| ISBN | : 1461304571 |
Download Mathematical Classification and Clustering Book in PDF, ePub and Kindle
I am very happy to have this opportunity to present the work of Boris Mirkin, a distinguished Russian scholar in the areas of data analysis and decision making methodologies. The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina torial optimization to biology, sociology and organizational structures. It compiles an immense amount of research done to date, including many original Russian de velopments never presented to the international community before (for instance, cluster-by-cluster versions of the K-Means method in Chapter 4 or uniform par titioning in Chapter 5). The author's approach, approximation clustering, allows him both to systematize a great part of the discipline and to develop many in novative methods in the framework of optimization problems. The optimization methods considered are proved to be meaningful in the contexts of data analysis and clustering. The material presented in this book is quite interesting and stimulating in paradigms, clustering and optimization. On the other hand, it has a substantial application appeal. The book will be useful both to specialists and students in the fields of data analysis and clustering as well as in biology, psychology, economics, marketing research, artificial intelligence, and other scientific disciplines. Panos Pardalos, Series Editor.
| Author | : Elizabeth Ann Maharaj |
| Publisher | : CRC Press |
| Total Pages | : 213 |
| Release | : 2019-03-19 |
| Genre | : Mathematics |
| ISBN | : 0429603304 |
Download Time Series Clustering and Classification Book in PDF, ePub and Kindle
The beginning of the age of artificial intelligence and machine learning has created new challenges and opportunities for data analysts, statisticians, mathematicians, econometricians, computer scientists and many others. At the root of these techniques are algorithms and methods for clustering and classifying different types of large datasets, including time series data. Time Series Clustering and Classification 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. Features Provides an overview of the methods and applications of pattern recognition of time series Covers a wide range of techniques, including unsupervised and supervised approaches Includes a range of real examples from medicine, finance, environmental science, and more R and MATLAB code, and relevant data sets are available on a supplementary website
| Author | : International Federation of Classification Societies. Conference |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 676 |
| Release | : 2004-06-09 |
| Genre | : Computers |
| ISBN | : 3540220143 |
Download Classification, Clustering, and Data Mining Applications Book in PDF, ePub and Kindle
Modern data analysis stands at the interface of statistics, computer science, and discrete mathematics. This volume describes new methods in this area, with special emphasis on classification and cluster analysis. Those methods are applied to problems in information retrieval, phylogeny, medical diagnosis, microarrays, and other active research areas.
| Author | : Ashok N. Srivastava |
| Publisher | : CRC Press |
| Total Pages | : 330 |
| Release | : 2009-06-15 |
| Genre | : Business & Economics |
| ISBN | : 1420059459 |
Download Text Mining Book in PDF, ePub and Kindle
The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the FieldGiving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify te
| Author | : Surekha Borra |
| Publisher | : Springer |
| Total Pages | : 97 |
| Release | : 2019-02-08 |
| Genre | : Technology & Engineering |
| ISBN | : 9811364249 |
Download Satellite Image Analysis: Clustering and Classification Book in PDF, ePub and Kindle
Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time. This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.
| Author | : Alan H. Fielding |
| Publisher | : Cambridge University Press |
| Total Pages | : 4 |
| Release | : 2006-12-14 |
| Genre | : Medical |
| ISBN | : 1139460064 |
Download Cluster and Classification Techniques for the Biosciences Book in PDF, ePub and Kindle
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 2006 book provides an overview of these important data analysis methods, from long-established statistical methods to more recent machine learning techniques. It aims to provide a framework that will enable the reader to recognise the assumptions and constraints that are implicit in all such techniques. Important generic issues are discussed first and then the major families of algorithms are described. Throughout the focus is on explanation and understanding and readers are directed to other resources that provide additional mathematical rigour when it is required. Examples taken from across the whole of biology, including bioinformatics, are provided throughout the book to illustrate the key concepts and each technique's potential.
| Author | : Michael W. Berry |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 251 |
| Release | : 2013-03-14 |
| Genre | : Computers |
| ISBN | : 147574305X |
Download Survey of Text Mining Book in PDF, ePub and Kindle
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 continues to grow, so does the need for designing robust, scalable indexing and search strategies (software) to meet a variety of user needs. Knowledge extraction or creation from text requires systematic yet reliable processing that can be codified and adapted for changing needs and environments. This book will draw upon experts in both academia and industry to recommend practical approaches to the purification, indexing, and mining of textual information. It will address document identification, clustering and categorizing documents, cleaning text, and visualizing semantic models of text.
