Foundations And Methods In Combinatorial And Statistical Data Analysis And Clustering

Foundations And Methods In Combinatorial And Statistical Data Analysis And Clustering Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Foundations And Methods In Combinatorial And Statistical Data Analysis And Clustering book. This book definitely worth reading, it is an incredibly well-written.

Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering

Israël César Lerman
Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering Book PDF

Author : Israël César Lerman
Publisher : Springer
Page : 647 pages
File Size : 55,6 Mb
Release : 2016-03-24
Category : Computers
ISBN : 9781447167938

Get Book

Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering by Israël César Lerman Pdf

This book offers an original and broad exploration of the fundamental methods in Clustering and Combinatorial Data Analysis, presenting new formulations and ideas within this very active field. With extensive introductions, formal and mathematical developments and real case studies, this book provides readers with a deeper understanding of the mutual relationships between these methods, which are clearly expressed with respect to three facets: logical, combinatorial and statistical. Using relational mathematical representation, all types of data structures can be handled in precise and unified ways which the author highlights in three stages: Clustering a set of descriptive attributes Clustering a set of objects or a set of object categories Establishing correspondence between these two dual clusterings Tools for interpreting the reasons of a given cluster or clustering are also included. Foundations and Methods in Combinatorial and Statistical Data Analysis and Clustering will be a valuable resource for students and researchers who are interested in the areas of Data Analysis, Clustering, Data Mining and Knowledge Discovery.

Seriation in Combinatorial and Statistical Data Analysis

Israël César Lerman,Henri Leredde
Seriation in Combinatorial and Statistical Data Analysis Book PDF

Author : Israël César Lerman,Henri Leredde
Publisher : Springer Nature
Page : 287 pages
File Size : 40,6 Mb
Release : 2022-03-04
Category : Computers
ISBN : 9783030926946

Get Book

Seriation in Combinatorial and Statistical Data Analysis by Israël César Lerman,Henri Leredde Pdf

This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering. Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically. State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods: Geometric representation methods Algorithmic and Combinatorial methods Original and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields.

Statistical Foundations of Data Science

Jianqing Fan,Runze Li,Cun-Hui Zhang,Hui Zou
Statistical Foundations of Data Science Book PDF

Author : Jianqing Fan,Runze Li,Cun-Hui Zhang,Hui Zou
Publisher : CRC Press
Page : 942 pages
File Size : 51,6 Mb
Release : 2020-09-21
Category : Mathematics
ISBN : 9780429527616

Get Book

Statistical Foundations of Data Science by Jianqing Fan,Runze Li,Cun-Hui Zhang,Hui Zou Pdf

Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.

Data Science

Francesco Palumbo,Angela Montanari,Maurizio Vichi
Data Science Book PDF

Author : Francesco Palumbo,Angela Montanari,Maurizio Vichi
Publisher : Springer
Page : 342 pages
File Size : 44,7 Mb
Release : 2017-07-04
Category : Mathematics
ISBN : 9783319557236

Get Book

Data Science by Francesco Palumbo,Angela Montanari,Maurizio Vichi Pdf

This edited volume on the latest advances in data science covers a wide range of topics in the context of data analysis and classification. In particular, it includes contributions on classification methods for high-dimensional data, clustering methods, multivariate statistical methods, and various applications. The book gathers a selection of peer-reviewed contributions presented at the Fifteenth Conference of the International Federation of Classification Societies (IFCS2015), which was hosted by the Alma Mater Studiorum, University of Bologna, from July 5 to 8, 2015.

Statistical Data Analytics

Walter W. Piegorsch
Statistical Data Analytics Book PDF

Author : Walter W. Piegorsch
Publisher : John Wiley & Sons
Page : 82 pages
File Size : 48,6 Mb
Release : 2015-08-17
Category : Mathematics
ISBN : 9781118619650

Get Book

Statistical Data Analytics by Walter W. Piegorsch Pdf

Statistical Data Analytics Statistical Data Analytics Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery Applications of data mining and ‘big data’ increasingly take center stage in our modern, knowledge-driven society, supported by advances in computing power, automated data acquisition, social media development and interactive, linkable internet software. This book presents a coherent, technical introduction to modern statistical learning and analytics, starting from the core foundations of statistics and probability. It includes an overview of probability and statistical distributions, basics of data manipulation and visualization, and the central components of standard statistical inferences. The majority of the text extends beyond these introductory topics, however, to supervised learning in linear regression, generalized linear models, and classification analytics. Finally, unsupervised learning via dimension reduction, cluster analysis, and market basket analysis are introduced. Extensive examples using actual data (with sample R programming code) are provided, illustrating diverse informatic sources in genomics, biomedicine, ecological remote sensing, astronomy, socioeconomics, marketing, advertising and finance, among many others. Statistical Data Analytics: Focuses on methods critically used in data mining and statistical informatics. Coherently describes the methods at an introductory level, with extensions to selected intermediate and advanced techniques. Provides informative, technical details for the highlighted methods. Employs the open-source R language as the computational vehicle – along with its burgeoning collection of online packages – to illustrate many of the analyses contained in the book. Concludes each chapter with a range of interesting and challenging homework exercises using actual data from a variety of informatic application areas. This book will appeal as a classroom or training text to intermediate and advanced undergraduates, and to beginning graduate students, with sufficient background in calculus and matrix algebra. It will also serve as a source-book on the foundations of statistical informatics and data analytics to practitioners who regularly apply statistical learning to their modern data.

Classification and Data Science in the Digital Age

Paula Brito,José G. Dias,Berthold Lausen,Angela Montanari,Rebecca Nugent
Classification and Data Science in the Digital Age Book PDF

Author : Paula Brito,José G. Dias,Berthold Lausen,Angela Montanari,Rebecca Nugent
Publisher : Springer Nature
Page : 393 pages
File Size : 54,5 Mb
Release : 2023-12-07
Category : Computers
ISBN : 9783031090349

Get Book

Classification and Data Science in the Digital Age by Paula Brito,José G. Dias,Berthold Lausen,Angela Montanari,Rebecca Nugent Pdf

The contributions gathered in this open access book focus on modern methods for data science and classification and present a series of real-world applications. Numerous research topics are covered, ranging from statistical inference and modeling to clustering and dimension reduction, from functional data analysis to time series analysis, and network analysis. The applications reflect new analyses in a variety of fields, including medicine, marketing, genetics, engineering, and education. The book comprises selected and peer-reviewed papers presented at the 17th Conference of the International Federation of Classification Societies (IFCS 2022), held in Porto, Portugal, July 19–23, 2022. The IFCS federates the classification societies and the IFCS biennial conference brings together researchers and stakeholders in the areas of Data Science, Classification, and Machine Learning. It provides a forum for presenting high-quality theoretical and applied works, and promoting and fostering interdisciplinary research and international cooperation. The intended audience is researchers and practitioners who seek the latest developments and applications in the field of data science and classification.

Branch-and-Bound Applications in Combinatorial Data Analysis

Michael J. Brusco,Stephanie Stahl
Branch and Bound Applications in Combinatorial Data Analysis Book PDF

Author : Michael J. Brusco,Stephanie Stahl
Publisher : Springer Science & Business Media
Page : 222 pages
File Size : 46,7 Mb
Release : 2005-11-30
Category : Mathematics
ISBN : 9780387288109

Get Book

Branch-and-Bound Applications in Combinatorial Data Analysis by Michael J. Brusco,Stephanie Stahl Pdf

This book provides clear explanatory text, illustrative mathematics and algorithms, demonstrations of the iterative process, pseudocode, and well-developed examples for applications of the branch-and-bound paradigm to important problems in combinatorial data analysis. Supplementary material, such as computer programs, are provided on the world wide web. Dr. Brusco is an editorial board member for the Journal of Classification, and a member of the Board of Directors for the Classification Society of North America.

Clustering and Classification

Phipps Arabie,Geert de Soete
Clustering and Classification Book PDF

Author : Phipps Arabie,Geert de Soete
Publisher : World Scientific
Page : 508 pages
File Size : 44,6 Mb
Release : 1996
Category : Mathematics
ISBN : 9810212879

Get Book

Clustering and Classification by Phipps Arabie,Geert de Soete Pdf

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.

Foundations of Statistics for Data Scientists

Alan Agresti,Maria Kateri
Foundations of Statistics for Data Scientists Book PDF

Author : Alan Agresti,Maria Kateri
Publisher : CRC Press
Page : 486 pages
File Size : 44,5 Mb
Release : 2021-11-22
Category : Business & Economics
ISBN : 9781000462913

Get Book

Foundations of Statistics for Data Scientists by Alan Agresti,Maria Kateri Pdf

Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.

Seriation in Combinatorial and Statistical Data Analysis

Israël César Lerman,Henri Leredde
Seriation in Combinatorial and Statistical Data Analysis Book PDF

Author : Israël César Lerman,Henri Leredde
Publisher : Unknown
Page : 0 pages
File Size : 52,5 Mb
Release : 2022
Category : Electronic
ISBN : 3030926958

Get Book

Seriation in Combinatorial and Statistical Data Analysis by Israël César Lerman,Henri Leredde Pdf

This monograph offers an original broad and very diverse exploration of the seriation domain in data analysis, together with building a specific relation to clustering. Relative to a data table crossing a set of objects and a set of descriptive attributes, the search for orders which correspond respectively to these two sets is formalized mathematically and statistically. State-of-the-art methods are created and compared with classical methods and a thorough understanding of the mutual relationships between these methods is clearly expressed. The authors distinguish two families of methods: Geometric representation methods Algorithmic and Combinatorial methods Original and accurate methods are provided in the framework for both families. Their basis and comparison is made on both theoretical and experimental levels. The experimental analysis is very varied and very comprehensive. Seriation in Combinatorial and Statistical Data Analysis has a unique character in the literature falling within the fields of Data Analysis, Data Mining and Knowledge Discovery. It will be a valuable resource for students and researchers in the latter fields.

Advanced Statistical Methods for the Analysis of Large Data-Sets

Agostino Di Ciaccio,Mauro Coli,Jose Miguel Angulo Ibanez
Advanced Statistical Methods for the Analysis of Large Data Sets Book PDF

Author : Agostino Di Ciaccio,Mauro Coli,Jose Miguel Angulo Ibanez
Publisher : Springer Science & Business Media
Page : 464 pages
File Size : 45,7 Mb
Release : 2012-03-05
Category : Mathematics
ISBN : 9783642210372

Get Book

Advanced Statistical Methods for the Analysis of Large Data-Sets by Agostino Di Ciaccio,Mauro Coli,Jose Miguel Angulo Ibanez Pdf

The theme of the meeting was “Statistical Methods for the Analysis of Large Data-Sets”. In recent years there has been increasing interest in this subject; in fact a huge quantity of information is often available but standard statistical techniques are usually not well suited to managing this kind of data. The conference serves as an important meeting point for European researchers working on this topic and a number of European statistical societies participated in the organization of the event. The book includes 45 papers from a selection of the 156 papers accepted for presentation and discussed at the conference on “Advanced Statistical Methods for the Analysis of Large Data-sets.”

Handbook of Cluster Analysis

Christian Hennig,Marina Meila,Fionn Murtagh,Roberto Rocci
Handbook of Cluster Analysis Book PDF

Author : Christian Hennig,Marina Meila,Fionn Murtagh,Roberto Rocci
Publisher : CRC Press
Page : 753 pages
File Size : 47,5 Mb
Release : 2015-12-16
Category : Business & Economics
ISBN : 9781466551893

Get Book

Handbook of Cluster Analysis by Christian Hennig,Marina Meila,Fionn Murtagh,Roberto Rocci Pdf

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

Data Analysis

Gérard Govaert
Data Analysis Book PDF

Author : Gérard Govaert
Publisher : John Wiley & Sons
Page : 265 pages
File Size : 49,9 Mb
Release : 2013-03-04
Category : Mathematics
ISBN : 9781118617861

Get Book

Data Analysis by Gérard Govaert Pdf

The first part of this book is devoted to methods seeking relevant dimensions of data. The variables thus obtained provide a synthetic description which often results in a graphical representation of the data. After a general presentation of the discriminating analysis, the second part is devoted to clustering methods which constitute another method, often complementary to the methods described in the first part, to synthesize and to analyze the data. The book concludes by examining the links existing between data mining and data analysis.

An Introduction to Clustering with R

Paolo Giordani,Maria Brigida Ferraro,Francesca Martella
An Introduction to Clustering with R Book PDF

Author : Paolo Giordani,Maria Brigida Ferraro,Francesca Martella
Publisher : Springer Nature
Page : 340 pages
File Size : 47,8 Mb
Release : 2020-08-27
Category : Mathematics
ISBN : 9789811305535

Get Book

An Introduction to Clustering with R by Paolo Giordani,Maria Brigida Ferraro,Francesca Martella Pdf

The purpose of this book is to thoroughly prepare the reader for applied research in clustering. Cluster analysis comprises a class of statistical techniques for classifying multivariate data into groups or clusters based on their similar features. Clustering is nowadays widely used in several domains of research, such as social sciences, psychology, and marketing, highlighting its multidisciplinary nature. This book provides an accessible and comprehensive introduction to clustering and offers practical guidelines for applying clustering tools by carefully chosen real-life datasets and extensive data analyses. The procedures addressed in this book include traditional hard clustering methods and up-to-date developments in soft clustering. Attention is paid to practical examples and applications through the open source statistical software R. Commented R code and output for conducting, step by step, complete cluster analyses are available. The book is intended for researchers interested in applying clustering methods. Basic notions on theoretical issues and on R are provided so that professionals as well as novices with little or no background in the subject will benefit from the book.

Cluster Analysis for Applications

Michael R. Anderberg
Cluster Analysis for Applications Book PDF

Author : Michael R. Anderberg
Publisher : Academic Press
Page : 376 pages
File Size : 41,9 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483191393

Get Book

Cluster Analysis for Applications by Michael R. Anderberg Pdf

Cluster Analysis for Applications deals with methods and various applications of cluster analysis. Topics covered range from variables and scales to measures of association among variables and among data units. Conceptual problems in cluster analysis are discussed, along with hierarchical and non-hierarchical clustering methods. The necessary elements of data analysis, statistics, cluster analysis, and computer implementation are integrated vertically to cover the complete path from raw data to a finished analysis. Comprised of 10 chapters, this book begins with an introduction to the subject of cluster analysis and its uses as well as category sorting problems and the need for cluster analysis algorithms. The next three chapters give a detailed account of variables and association measures, with emphasis on strategies for dealing with problems containing variables of mixed types. Subsequent chapters focus on the central techniques of cluster analysis with particular reference to computational considerations; interpretation of clustering results; and techniques and strategies for making the most effective use of cluster analysis. The final chapter suggests an approach for the evaluation of alternative clustering methods. The presentation is capped with a complete set of implementing computer programs listed in the Appendices to make the use of cluster analysis as painless and free of mechanical error as is possible. This monograph is intended for students and workers who have encountered the notion of cluster analysis.