Data Mining with R

Data Mining with R

Author: Luis Torgo

Publisher: CRC Press

Published: 2016-11-30

Total Pages: 426

ISBN-13: 1315399091

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Data Mining with R: Learning with Case Studies, Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition, this new edition is divided into two parts. The first part will feature introductory material, including a new chapter that provides an introduction to data mining, to complement the already existing introduction to R. The second part includes case studies, and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies, and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book’s web site. These files include all the code used in the case studies, and they facilitate the "do-it-yourself" approach followed in the book. Designed for users of data analysis tools, as well as researchers and developers, the book should be useful for anyone interested in entering the "world" of R and data mining. About the Author Luís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business’ MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years, Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA.


Advances in Knowledge Discovery and Data Mining

Advances in Knowledge Discovery and Data Mining

Author: Usama M. Fayyad

Publisher:

Published: 1996

Total Pages: 638

ISBN-13:

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Eight sections of this book span fundamental issues of knowledge discovery, classification and clustering, trend and deviation analysis, dependency derivation, integrated discovery systems, augumented database systems and application case studies. The appendices provide a list of terms used in the literature of the field of data mining and knowledge discovery in databases, and a list of online resources for the KDD researcher.


Knowledge Discovery in the Social Sciences

Knowledge Discovery in the Social Sciences

Author: Xiaoling Shu

Publisher: University of California Press

Published: 2020-02-04

Total Pages: 263

ISBN-13: 0520339991

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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


Knowledge Discovery and Data Mining

Knowledge Discovery and Data Mining

Author: O. Maimon

Publisher: Springer Science & Business Media

Published: 2000-12-31

Total Pages: 192

ISBN-13: 9780792366478

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This book presents a specific and unified approach to Knowledge Discovery and Data Mining, termed IFN for Information Fuzzy Network methodology. Data Mining (DM) is the science of modelling and generalizing common patterns from large sets of multi-type data. DM is a part of KDD, which is the overall process for Knowledge Discovery in Databases. The accessibility and abundance of information today makes this a topic of particular importance and need. The book has three main parts complemented by appendices as well as software and project data that are accessible from the book's web site (http://www.eng.tau.ac.iV-maimonlifn-kdg£). Part I (Chapters 1-4) starts with the topic of KDD and DM in general and makes reference to other works in the field, especially those related to the information theoretic approach. The remainder of the book presents our work, starting with the IFN theory and algorithms. Part II (Chapters 5-6) discusses the methodology of application and includes case studies. Then in Part III (Chapters 7-9) a comparative study is presented, concluding with some advanced methods and open problems. The IFN, being a generic methodology, applies to a variety of fields, such as manufacturing, finance, health care, medicine, insurance, and human resources. The appendices expand on the relevant theoretical background and present descriptions of sample projects (including detailed results).


Cases on Research and Knowledge Discovery: Homeland Security Centers of Excellence

Cases on Research and Knowledge Discovery: Homeland Security Centers of Excellence

Author: Brown, Cecelia Wright

Publisher: IGI Global

Published: 2014-04-30

Total Pages: 357

ISBN-13: 1466659475

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To ensure its protection from enemies both foreign and domestic, a government must invest resources and personnel toward the goal of homeland security. It is through these endeavors that citizens are able to live out their lives in peace. Cases on Research and Knowledge Discovery: Homeland Security Centers of Excellence presents a series of studies and descriptive examples on the US Department of Homeland Security and related research. Through its investigation of interesting challenges and thought-provoking ideas, this volume offers professionals, researchers, and academics in the fields of security science, engineering, technology, and mathematics an in-depth discussion of some of the issues that directly affect the safety, security, and prosperity of the nation.


Urban Informatics

Urban Informatics

Author: Wenzhong Shi

Publisher: Springer Nature

Published: 2021-04-06

Total Pages: 941

ISBN-13: 9811589836

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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.


Geographic Data Mining and Knowledge Discovery

Geographic Data Mining and Knowledge Discovery

Author: Harvey J. Miller

Publisher: CRC Press

Published: 2009-05-27

Total Pages: 486

ISBN-13: 1420073982

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The Definitive Volume on Cutting-Edge Exploratory Analysis of Massive Spatial and Spatiotemporal DatabasesSince the publication of the first edition of Geographic Data Mining and Knowledge Discovery, new techniques for geographic data warehousing (GDW), spatial data mining, and geovisualization (GVis) have been developed. In addition, there has bee


Privacy-Aware Knowledge Discovery

Privacy-Aware Knowledge Discovery

Author: Francesco Bonchi

Publisher: CRC Press

Published: 2010-12-02

Total Pages: 527

ISBN-13: 1439803668

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Covering research at the frontier of this field, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques presents state-of-the-art privacy-preserving data mining techniques for application domains, such as medicine and social networks, that face the increasing heterogeneity and complexity of new forms of data. Renowned authorities


Data Mining and Medical Knowledge Management: Cases and Applications

Data Mining and Medical Knowledge Management: Cases and Applications

Author: Berka, Petr

Publisher: IGI Global

Published: 2009-02-28

Total Pages: 464

ISBN-13: 1605662194

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The healthcare industry produces a constant flow of data, creating a need for deep analysis of databases through data mining tools and techniques resulting in expanded medical research, diagnosis, and treatment. Data Mining and Medical Knowledge Management: Cases and Applications presents case studies on applications of various modern data mining methods in several important areas of medicine, covering classical data mining methods, elaborated approaches related to mining in electroencephalogram and electrocardiogram data, and methods related to mining in genetic data. A premier resource for those involved in data mining and medical knowledge management, this book tackles ethical issues related to cost-sensitive learning in medicine and produces theoretical contributions concerning general problems of data, information, knowledge, and ontologies.