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28 produkter
28 produkter
Häftad, Engelska, 2019
1 002 kr
Skickas inom 10-15 vardagar
Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data world that we inhabit.Statistical Learning and Data Science is a work of reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology. The book also addresses issues of origin and evolutions in the unsupervised data analysis arena, and presents some approaches for time series, symbolic data, and functional data.Over the history of multidimensional data analysis, more and more complex data have become available for processing. Supervised machine learning, semi-supervised analysis approaches, and unsupervised data analysis, provide great capability for addressing the digital data deluge. Exploring the foundations and recent breakthroughs in the field, Statistical Learning and Data Science demonstrates how data analysis can improve personal and collective health and the well-being of our social, business, and physical environments.
Häftad, Engelska, 2019
1 032 kr
Skickas inom 10-15 vardagar
Developed by Jean-Paul Benzérci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater than ever.Correspondence Analysis and Data Coding with Java and R clearly demonstrates why this technique remains important and in the eyes of many, unsurpassed as an analysis framework. After presenting some historical background, the author presents a theoretical overview of the mathematics and underlying algorithms of correspondence analysis and hierarchical clustering. The focus then shifts to data coding, with a survey of the widely varied possibilities correspondence analysis offers and introduction of the Java software for correspondence analysis, clustering, and interpretation tools. A chapter of case studies follows, wherein the author explores applications to areas such as shape analysis and time-evolving data. The final chapter reviews the wealth of studies on textual content as well as textual form, carried out by Benzécri and his research lab. These discussions show the importance of correspondence analysis to artificial intelligence as well as to stylometry and other fields.This book not only shows why correspondence analysis is important, but with a clear presentation replete with advice and guidance, also shows how to put this technique into practice. Downloadable software and data sets allow quick, hands-on exploration of innovative correspondence analysis applications.
Häftad, Engelska, 2020
1 128 kr
Skickas inom 10-15 vardagar
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.
Häftad, Engelska, 2020
778 kr
Skickas inom 10-15 vardagar
"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in my teaching."- Mark Girolami, Warwick UniversityData Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge.
E-bok
PDF, Engelska, 2007712 kr
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Intelligent information Retrieval comprehensively surveys scientific information retrieval, which is characterized by growing convergence of information expressed in varying complementary forms of data - textual, numerical, image, and graphics; by the fundamental transformation which the scientific library is currently being subjected to; and by computer networking which as become an essential element of the research fabric. Intelligent Information Retrieval addresses enabling technologies, so-called `wide area network resource discovery tools'', and the state of the art in astronomy and other sciences. This work is essential reading for astronomers, scientists in related disciplines, and all those involved in information storage and retrieval.
E-bok
Engelska, 20111 194 kr
Läs direkt efter köp
Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data wor
E-bok
Engelska, 20151 278 kr
Läs direkt efter köp
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
E-bok
Engelska, 20051 194 kr
Läs direkt efter köp
Developed by Jean-Paul Benzerci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater
Sparse Image and Signal Processing
Wavelets and Related Geometric Multiscale Analysis, Second Edition
Inbunden, Engelska, 2015
1 070 kr
Skickas inom 7-10 vardagar
This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency's Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.
E-bok
Engelska, 2017925 kr
Läs direkt efter köp
"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in my teaching."- Mark Girolami, Warwick University
Data Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge.
Sparse Image and Signal Processing
Wavelets and Related Geometric Multiscale Analysis, Second Edition
E-bok
Engelska, 20151 288 kr
Läs direkt efter köp
This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency''s Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.
Sparse Image and Signal Processing
Wavelets and Related Geometric Multiscale Analysis, Second Edition
E-bok
PDF, Engelska, 20151 288 kr
Läs direkt efter köp
This thoroughly updated new edition presents state-of-the-art sparse and multiscale image and signal processing. It covers linear multiscale geometric transforms, such as wavelet, ridgelet, or curvelet transforms, and non-linear multiscale transforms based on the median and mathematical morphology operators. Along with an up-to-the-minute description of required computation, it covers the latest results in inverse problem solving and regularization, sparse signal decomposition, blind source separation, in-painting, and compressed sensing. New chapters and sections cover multiscale geometric transforms for three-dimensional data (data cubes), data on the sphere (geo-located data), dictionary learning, and nonnegative matrix factorization. The authors wed theory and practice in examining applications in areas such as astronomy, including recent results from the European Space Agency''s Herschel mission, biology, fusion physics, cold dark matter simulation, medical MRI, digital media, and forensics. MATLAB® and IDL code, available online at www.SparseSignalRecipes.info, accompany these methods and all applications.
E-bok
PDF, Engelska, 20051 229 kr
Läs direkt efter köp
Developed by Jean-Paul Benzerci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater
Inbunden, Engelska, 2011
2 104 kr
Skickas inom 10-15 vardagar
Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data world that we inhabit.Statistical Learning and Data Science is a work of reference in the rapidly evolving context of converging methodologies. It gathers contributions from some of the foundational thinkers in the different fields of data analysis to the major theoretical results in the domain. On the methodological front, the volume includes conformal prediction and frameworks for assessing confidence in outputs, together with attendant risk. It illustrates a wide range of applications, including semantics, credit risk, energy production, genomics, and ecology. The book also addresses issues of origin and evolutions in the unsupervised data analysis arena, and presents some approaches for time series, symbolic data, and functional data.Over the history of multidimensional data analysis, more and more complex data have become available for processing. Supervised machine learning, semi-supervised analysis approaches, and unsupervised data analysis, provide great capability for addressing the digital data deluge. Exploring the foundations and recent breakthroughs in the field, Statistical Learning and Data Science demonstrates how data analysis can improve personal and collective health and the well-being of our social, business, and physical environments.
E-bok
PDF, Engelska, 20111 194 kr
Läs direkt efter köp
Data analysis is changing fast. Driven by a vast range of application domains and affordable tools, machine learning has become mainstream. Unsupervised data analysis, including cluster analysis, factor analysis, and low dimensionality mapping methods continually being updated, have reached new heights of achievement in the incredibly rich data wor
Inbunden, Engelska, 2015
3 633 kr
Skickas inom 10-15 vardagar
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.
E-bok
PDF, Engelska, 20151 345 kr
Läs direkt efter köp
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
Inbunden, Engelska, 2017
1 457 kr
Skickas inom 10-15 vardagar
"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in my teaching."- Mark Girolami, Warwick UniversityData Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge.
E-bok
PDF, Engelska, 2017925 kr
Läs direkt efter köp
"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in my teaching."- Mark Girolami, Warwick University
Data Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge.
Inbunden, Engelska, 2024
2 215 kr
Skickas inom 10-15 vardagar
This book explores current research and development in the area of digital healthcare using recent technologies such as data science and artificial intelligence. The authors discuss how data science, AI, and mobile technologies provide the fundamental backbone to digital healthcare, presenting each technology separately as well covering integrated solutions. The book also focuses on the integration of different multi-disciplinary approaches along with examples and case studies. In order to identify the challenges with security and privacy issues, relevant block chain technologies are identified and discussed. Social aspects related to digital solutions and platforms for healthcare are also discussed and analyzed. The book aims to present high quality, technical contributions in the field of mobile digital healthcare using technologies such as AI, deep learning, IoT and distributed cloud computing.
E-bok
Engelska, 20242 840 kr
Läs direkt efter köp
This book explores current research and development in the area of digital healthcare using recent technologies such as data science and artificial intelligence. The authors discuss how data science, AI, and mobile technologies provide the fundamental backbone to digital healthcare, presenting each technology separately as well covering integrated solutions. The book also focuses on the integration of different multi-disciplinary approaches along with examples and case studies. In order to identify the challenges with security and privacy issues, relevant block chain technologies are identified and discussed. Social aspects related to digital solutions and platforms for healthcare are also discussed and analyzed. The book aims to present high quality, technical contributions in the field of mobile digital healthcare using technologies such as AI, deep learning, IoT and distributed cloud computing.
Del 11018 - Lecture Notes in Computer Science
Experimental IR Meets Multilinguality, Multimodality, and Interaction
9th International Conference of the CLEF Association, CLEF 2018, Avignon, France, September 10-14, 2018, Proceedings
Häftad, Engelska, 2018
561 kr
Skickas inom 10-15 vardagar
This book constitutes the refereed proceedings of the 9th International Conference of the CLEF Initiative, CLEF 2018, jointly organized by Avignon, Marseille and Toulon universities and held in Avignon, France, in September 2018. The conference has a clear focus on experimental information retrieval with special attention to the challenges of multimodality, multilinguality, and interactive search ranging from unstructured to semi structures and structured data. The 13 papers presented in this volume were carefully reviewed and selected from 39 submissions. Many papers tackle the medical ehealth and ehealth multimedia retrieval challenges, however there are many other topics of research such as document clustering, social biases in IR, social book search, personality profiling. Further this volume presents 9 “best of the labs” papers which were reviewed as a full paper submission with the same review criteria. The labs represented scientific challenges based on new data setsand real world problems in multimodal and multilingual information access. In addition to this, 10 benchmarking labs reported results of their yearlong activities in overview talks and lab sessions. The papers address all aspects of information access in any modularity and language and cover a broad range of topics in the field of multilingual and multimodal information access evaluation.
734 kr
Läs direkt efter köp
This book constitutes the refereed proceedings of the 9th International Conference of the CLEF Initiative, CLEF 2018, jointly organized by Avignon, Marseille and Toulon universities and held in Avignon, France, in September 2018. The conference has a clear focus on experimental information retrieval with special attention to the challenges of multimodality, multilinguality, and interactive search ranging from unstructured to semi structures and structured data. The 13 papers presented in this volume were carefully reviewed and selected from 39 submissions. Many papers tackle the medical ehealth and ehealth multimedia retrieval challenges, however there are many other topics of research such as document clustering, social biases in IR, social book search, personality profiling. Further this volume presents 9 “best of the labs” papers which were reviewed as a full paper submission with the same review criteria. The labs represented scientific challenges based on new data setsand real world problems in multimodal and multilingual information access. In addition to this, 10 benchmarking labs reported results of their yearlong activities in overview talks and lab sessions. The papers address all aspects of information access in any modularity and language and cover a broad range of topics in the field of multilingual and multimodal information access evaluation.
Häftad, Engelska, 2014
545 kr
Skickas inom 10-15 vardagar
This book gives a synthesis of the state of the art in artificial intelligence in astronomy and astrophysics, presents its current applications and points out directions of future work. The individual chapters report on the application of artificial intelligence techniques for large astronomical surveys, for processing cosmic ray data, for facilitating data reduction using image processing systems, for telescope scheduling, for observatory ground support operations, for observation proposal preparation assistance, and for scientific applications such as stellar spectral and galaxy morphology classification. The new field of connectionism (neural networks) is also surveyed. The book is designed to be self-contained: a glossary of terms used in this area is provided and an index of terms, acronyms and proper names completes the book.
Del 131 - Astrophysics and Space Science Library
Multivariate Data Analysis
Häftad, Engelska, 1987
1 621 kr
Skickas inom 10-15 vardagar
Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue. This book fills the gap by providing a presentation of the most useful techniques in multivariate statistics. A wide-ranging annotated set of general and astronomical bibliographic references follows each chapter, providing valuable entry-points for research workers in all astronomical sub-disciplines. Although the applications considered focus on astronomy, the algorithms used can be applied to similar problems in other branches of science. Fortran programs are provided for many of the methods described.
E-bok
PDF, Engelska, 20122 049 kr
Läs direkt efter köp
Interest in statistical methodology is increasing so rapidly in the astronomical community that accessible introductory material in this area is long overdue. This book fills the gap by providing a presentation of the most useful techniques in multivariate statistics. A wide-ranging annotated set of general and astronomical bibliographic references follows each chapter, providing valuable entry-points for research workers in all astronomical sub-disciplines. Although the applications considered focus on astronomy, the algorithms used can be applied to similar problems in other branches of science. Fortran programs are provided for many of the methods described.
Del 182 - Astrophysics and Space Science Library
Intelligent Information Retrieval: The Case of Astronomy and Related Space Sciences
Häftad, Engelska, 2013
545 kr
Skickas inom 10-15 vardagar
Intelligent information Retrieval comprehensively surveys scientific information retrieval, which is characterized by growing convergence of information expressed in varying complementary forms of data - textual, numerical, image, and graphics; by the fundamental transformation which the scientific library is currently being subjected to; and by computer networking which as become an essential element of the research fabric.Intelligent Information Retrieval addresses enabling technologies, so-called `wide area network resource discovery tools', and the state of the art in astronomy and other sciences.This work is essential reading for astronomers, scientists in related disciplines, and all those involved in information storage and retrieval.
Inbunden, Engelska, 2005
1 366 kr
Tillfälligt slut
Developed by Jean-Paul Benzérci more than 30 years ago, correspondence analysis as a framework for analyzing data quickly found widespread popularity in Europe. The topicality and importance of correspondence analysis continue, and with the tremendous computing power now available and new fields of application emerging, its significance is greater than ever.Correspondence Analysis and Data Coding with Java and R clearly demonstrates why this technique remains important and in the eyes of many, unsurpassed as an analysis framework. After presenting some historical background, the author presents a theoretical overview of the mathematics and underlying algorithms of correspondence analysis and hierarchical clustering. The focus then shifts to data coding, with a survey of the widely varied possibilities correspondence analysis offers and introduction of the Java software for correspondence analysis, clustering, and interpretation tools. A chapter of case studies follows, wherein the author explores applications to areas such as shape analysis and time-evolving data. The final chapter reviews the wealth of studies on textual content as well as textual form, carried out by Benzécri and his research lab. These discussions show the importance of correspondence analysis to artificial intelligence as well as to stylometry and other fields.This book not only shows why correspondence analysis is important, but with a clear presentation replete with advice and guidance, also shows how to put this technique into practice. Downloadable software and data sets allow quick, hands-on exploration of innovative correspondence analysis applications.