Mathematical Classification And Clustering PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Mathematical Classification And Clustering PDF full book. Access full book title Mathematical Classification And Clustering.
| 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 | : J. Van Ryzin |
| Publisher | : Elsevier |
| Total Pages | : 478 |
| Release | : 2014-05-10 |
| Genre | : Mathematics |
| ISBN | : 1483276619 |
Download Classification and Clustering Book in PDF, ePub and Kindle
Classification and Clustering documents the proceedings of the Advanced Seminar on Classification and Clustering held in Madison, Wisconsin on May 3-5, 1976. This compilation discusses the relationship between multidimensional scaling and clustering, distribution problems in clustering, and botryology of botryology. The graph theoretic techniques for cluster analysis algorithms, data dependent clustering techniques, and linguistic approach to pattern recognition are also elaborated. This text likewise covers the discriminant analysis when scale contamination is present in the initial sample and statistical basis of computerized diagnosis using the electrocardiogram. Other topics include the simple histogram method for nonparametric classification and optimal smoothing of density estimates. This book is intended for mathematicians, biological scientists, social scientists, computer scientists, statisticians, and engineers interested in classification and clustering.
| Author | : Daniela Calvetti |
| Publisher | : SIAM |
| Total Pages | : 199 |
| Release | : 2020-11-20 |
| Genre | : Mathematics |
| ISBN | : 1611976375 |
Download Mathematics of Data Science: A Computational Approach to Clustering and Classification Book in PDF, ePub and Kindle
This textbook provides a solid mathematical basis for understanding popular data science algorithms for clustering and classification and shows that an in-depth understanding of the mathematics powering these algorithms gives insight into the underlying data. It presents a step-by-step derivation of these algorithms, outlining their implementation from scratch in a computationally sound way. Mathematics of Data Science: A Computational Approach to Clustering and Classification proposes different ways of visualizing high-dimensional data to unveil hidden internal structures, and nearly every chapter includes graphical explanations and computed examples using publicly available data sets to highlight similarities and differences among the algorithms. This self-contained book is geared toward advanced undergraduate and beginning graduate students in the mathematical sciences, engineering, and computer science and can be used as the main text in a semester course. Researchers in any application area where data science methods are used will also find the book of interest. No advanced mathematical or statistical background is assumed.
| Author | : Phips Arabie |
| Publisher | : World Scientific |
| Total Pages | : 501 |
| Release | : 1996-01-29 |
| Genre | : Computers |
| ISBN | : 981450453X |
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 | : David Banks |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 642 |
| Release | : 2011-01-07 |
| Genre | : Language Arts & Disciplines |
| ISBN | : 3642171036 |
Download Classification, Clustering, and Data Mining Applications Book in PDF, ePub and Kindle
This volume describes new methods with special emphasis on classification and cluster analysis. These methods are applied to problems in information retrieval, phylogeny, medical diagnosis, microarrays, and other active research areas.
| 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 | : John Van Ryzin |
| Publisher | : |
| Total Pages | : 467 |
| Release | : 1977 |
| Genre | : Cluster analysis |
| ISBN | : 9780127142500 |
Download Classification and Clustering Book in PDF, ePub and Kindle
Clustering and classification: background and current directions; The relationship between multidimensional scaling and clustering; Distribution problems in clustering; The botryology of botryology; Graph theoretic techniques for cluster analysis algorithms; An empirical comparison of baseline models for goodness-of-fit in r-diameter hierarchical clustering; Data dependent clustering techniques; Cluster analysis applied to a study of race mixture in human populations; Linguistic approach to pattern recognition; Fuzzy sets and their application to pattern classification and clustering analysis; Discrimination, allocatory and separatory, linear aspects; Discriminant analysis when scale contamination is present in the initial sample; The statistical basis of computerrized diagnosis using the electrocardiogram; Linear discrimination some further results on best lower dimensional representations; A simple histogram method for nonparametric classification; Optimal smoothing of density estimates.
| Author | : Guojun Gan |
| Publisher | : SIAM |
| Total Pages | : 430 |
| Release | : 2020-11-10 |
| Genre | : Mathematics |
| ISBN | : 1611976332 |
Download Data Clustering: Theory, Algorithms, and Applications, Second Edition Book in PDF, ePub and Kindle
Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
| 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 | : 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
