Statistical Data Mining And Knowledge Discovery
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Statistical Data Mining And Knowledge Discovery
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Author : Hamparsum Bozdogan
language : en
Publisher: CRC Press
Release Date : 2003-07-29
Statistical Data Mining And Knowledge Discovery written by Hamparsum Bozdogan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-29 with Business & Economics categories.
Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approaches that meld concepts, tools, and techniques from diverse areas, such as computer science, statistics, artificial intelligence, and financial engineering. Statistical Data Mining and Knowledge Discovery brings together a stellar panel of experts to discuss and disseminate recent developments in data analysis techniques for data mining and knowledge extraction. This carefully edited collection provides a practical, multidisciplinary perspective on using statistical techniques in areas such as market segmentation, customer profiling, image and speech analysis, and fraud detection. The chapter authors, who include such luminaries as Arnold Zellner, S. James Press, Stephen Fienberg, and Edward K. Wegman, present novel approaches and innovative models and relate their experiences in using data mining techniques in a wide range of applications.
Statistical Data Mining And Knowledge Discovery
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Author : Hamparsum Bozdogan
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2003-07-29
Statistical Data Mining And Knowledge Discovery written by Hamparsum Bozdogan and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-07-29 with Business & Economics categories.
Massive data sets pose a great challenge to many cross-disciplinary fields, including statistics. The high dimensionality and different data types and structures have now outstripped the capabilities of traditional statistical, graphical, and data visualization tools. Extracting useful information from such large data sets calls for novel approaches that meld concepts, tools, and techniques from diverse areas, such as computer science, statistics, artificial intelligence, and financial engineering. Statistical Data Mining and Knowledge Discovery brings together a stellar panel of experts to discuss and disseminate recent developments in data analysis techniques for data mining and knowledge extraction. This carefully edited collection provides a practical, multidisciplinary perspective on using statistical techniques in areas such as market segmentation, customer profiling, image and speech analysis, and fraud detection. The chapter authors, who include such luminaries as Arnold Zellner, S. James Press, Stephen Fienberg, and Edward K. Wegman, present novel approaches and innovative models and relate their experiences in using data mining techniques in a wide range of applications.
Statistical Data Analytics
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Author : Walter W. Piegorsch
language : en
Publisher: John Wiley & Sons
Release Date : 2016-03-22
Statistical Data Analytics written by Walter W. Piegorsch and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-22 with Mathematics categories.
Solutions Manual to accompany Statistical Data Analytics: Foundations for Data Mining, Informatics, and Knowledge Discovery A comprehensive introduction to statistical methods for data mining and knowledge discovery. Extensive solutions 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.
Data Mining
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Author : Krzysztof J. Cios
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-10-05
Data Mining written by Krzysztof J. Cios and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-10-05 with Computers categories.
“If you torture the data long enough, Nature will confess,” said 1991 Nobel-winning economist Ronald Coase. The statement is still true. However, achieving this lofty goal is not easy. First, “long enough” may, in practice, be “too long” in many applications and thus unacceptable. Second, to get “confession” from large data sets one needs to use state-of-the-art “torturing” tools. Third, Nature is very stubborn — not yielding easily or unwilling to reveal its secrets at all. Fortunately, while being aware of the above facts, the reader (a data miner) will find several efficient data mining tools described in this excellent book. The book discusses various issues connecting the whole spectrum of approaches, methods, techniques and algorithms falling under the umbrella of data mining. It starts with data understanding and preprocessing, then goes through a set of methods for supervised and unsupervised learning, and concludes with model assessment, data security and privacy issues. It is this specific approach of using the knowledge discovery process that makes this book a rare one indeed, and thus an indispensable addition to many other books on data mining. To be more precise, this is a book on knowledge discovery from data. As for the data sets, the easy-to-make statement is that there is no part of modern human activity left untouched by both the need and the desire to collect data. The consequence of such a state of affairs is obvious.
Urban Informatics
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Author : Wenzhong Shi
language : en
Publisher: Springer Nature
Release Date : 2021-04-06
Urban Informatics written by Wenzhong Shi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-06 with Social Science categories.
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
Knowledge Discovery In The Social Sciences
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Author : Xiaoling Shu
language : en
Publisher: University of California Press
Release Date : 2020-02-04
Knowledge Discovery In The Social Sciences written by Xiaoling Shu and has been published by University of California Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-04 with Social Science categories.
Knowledge Discovery in the Social Sciences helps readers find valid, meaningful, and useful information. It is written for researchers and data analysts as well as students who have no prior experience in statistics or computer science. Suitable for a variety of classes—including upper-division courses for undergraduates, introductory courses for graduate students, and courses in data management and advanced statistical methods—the book guides readers in the application of data mining techniques and illustrates the significance of newly discovered knowledge. Readers will learn to: • appreciate the role of data mining in scientific research • develop an understanding of fundamental concepts of data mining and knowledge discovery • use software to carry out data mining tasks • select and assess appropriate models to ensure findings are valid and meaningful • develop basic skills in data preparation, data mining, model selection, and validation • apply concepts with end-of-chapter exercises and review summaries
Handbook Of Statistical Analysis And Data Mining Applications
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Author : Ken Yale
language : en
Publisher: Elsevier
Release Date : 2017-11-09
Handbook Of Statistical Analysis And Data Mining Applications written by Ken Yale and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-09 with Mathematics categories.
Handbook of Statistical Analysis and Data Mining Applications, Second Edition, is a comprehensive professional reference book that guides business analysts, scientists, engineers and researchers, both academic and industrial, through all stages of data analysis, model building and implementation. The handbook helps users discern technical and business problems, understand the strengths and weaknesses of modern data mining algorithms and employ the right statistical methods for practical application. This book is an ideal reference for users who want to address massive and complex datasets with novel statistical approaches and be able to objectively evaluate analyses and solutions. It has clear, intuitive explanations of the principles and tools for solving problems using modern analytic techniques and discusses their application to real problems in ways accessible and beneficial to practitioners across several areas—from science and engineering, to medicine, academia and commerce. - Includes input by practitioners for practitioners - Includes tutorials in numerous fields of study that provide step-by-step instruction on how to use supplied tools to build models - Contains practical advice from successful real-world implementations - Brings together, in a single resource, all the information a beginner needs to understand the tools and issues in data mining to build successful data mining solutions - Features clear, intuitive explanations of novel analytical tools and techniques, and their practical applications
Data Mining And Knowledge Discovery Handbook
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Author : Oded Maimon
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-28
Data Mining And Knowledge Discovery Handbook written by Oded Maimon and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-28 with Computers categories.
Data Mining and Knowledge Discovery Handbook organizes all major concepts, theories, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery in databases (KDD) into a coherent and unified repository. This book first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. This volume concludes with in-depth descriptions of data mining applications in various interdisciplinary industries including finance, marketing, medicine, biology, engineering, telecommunications, software, and security. Data Mining and Knowledge Discovery Handbook is designed for research scientists and graduate-level students in computer science and engineering. This book is also suitable for professionals in fields such as computing applications, information systems management, and strategic research management.
Data Mining And Knowledge Discovery With Evolutionary Algorithms
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Author : Alex A. Freitas
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-11-11
Data Mining And Knowledge Discovery With Evolutionary Algorithms written by Alex A. Freitas and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-11-11 with Computers categories.
This book addresses the integration of two areas of computer science, namely data mining and evolutionary algorithms. Both these areas have become increas ingly popular in the last few years, and their integration is currently an area of active research. In essence, data mining consists of extracting valid, comprehensible, and in teresting knowledge from data. Data mining is actually an interdisciplinary field, since there are many kinds of methods that can be used to extract knowledge from data. Arguably, data mining mainly uses methods from machine learning (a branch of artificial intelligence) and statistics (including statistical pattern recog nition). Our discussion of data mining and evolutionary algorithms is primarily based on machine learning concepts and principles. In particular, in this book we emphasize the importance of discovering comprehensible, interesting knowledge, which the user can potentially use to make intelligent decisions. In a nutshell, the motivation for applying evolutionary algorithms to data mining is that evolutionary algorithms are robust search methods which perform a global search in the space of candidate solutions (rules or another form of knowl edge representation). In contrast, most rule induction methods perform a local, greedy search in the space of candidate rules. Intuitively, the global search of evolutionary algorithms can discover interesting rules and patterns that would be missed by the greedy search.
Data Mining With R
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Author : Luís Torgo
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2017
Data Mining With R written by Luís Torgo and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Business & Economics categories.
5.1 Problem Description and Objectives