Data Mining and Multi-agent Integration, Longbing Cao
Автор: Foster Provost Название: Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking ISBN: 1449361323 ISBN-13(EAN): 9781449361327 Издательство: Wiley Рейтинг: Цена: 6334.00 р. Наличие на складе: Есть (1 шт.) Описание: This broad, deep, but not-too-technical guide introduces you to the fundamental principles of data science and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect.
Описание: Like the popular second edition, Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. Inside, you'll learn all you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining?including both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. <br><br>Complementing the book is a fully functional platform-independent open source Weka software for machine learning, available for free download. <br><br>The book is a major revision of the second edition that appeared in 2005. While the basic core remains the same, it has been updated to reflect the changes that have taken place over the last four or five years. The highlights for the updated new edition include completely revised technique sections; new chapter on Data Transformations, new chapter on Ensemble Learning, new chapter on Massive Data Sets, a new ?book release? version of the popular Weka machine learning open source software (developed by the authors and specific to the Third Edition); new material on ?multi-instance learning?; new information on ranking the classification, plus comprehensive updates and modernization throughout. All in all, approximately 100 pages of new material.<br> <br><br>* Thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques<br><br>* Algorithmic methods at the heart of successful data mining?including tired and true methods as well as leading edge methods<br><br>* Performance improvement techniques that work by transforming the input or output<br><br>* Downloadable Weka, a collection of machine learning algorithms for data mining tasks, including tools for data pre-processing, classification, regression, clustering, association rules, and visualization?in an updated, interactive interface. <br>
Автор: Torgo Название: Data Mining with R ISBN: 1439810184 ISBN-13(EAN): 9781439810187 Издательство: Taylor&Francis Рейтинг: Цена: 9951.00 р. Наличие на складе: Нет в наличии.
Описание: This hands-on book uses practical examples to illustrate the power of R and data mining. Assuming no prior knowledge of R or data mining/statistical techniques, it covers a diverse set of problems that pose different challenges in terms of size, type of data, goals of analysis, and analytical tools. The main data mining processes and techniques are presented through detailed, real-world case studies. With these case studies, the author supplies all necessary steps, code, and data. Mirroring the do-it-yourself approach of the text, the supporting website provides data sets and R code.
Автор: С.Aggarwal Название: Data Mining: The Textbook ISBN: 3319141414 ISBN-13(EAN): 9783319141411 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Нет в наличии.
Описание: This textbook explores the different aspects of data mining from the fundamentals to the complex data types and their applications, capturing the wide diversity of problem domains for data mining issues.
Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.
Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.
Please visit the book companion website at https: //www.cs.waikato.ac.nz/ ml/weka/book.html.
It contains
Powerpoint slides for Chapters 1-12. This is a very comprehensive teaching resource, with many PPT slides covering each chapter of the book
Online Appendix on the Weka workbench; again a very comprehensive learning aid for the open source software that goes with the book
Table of contents, highlighting the many new sections in the 4th edition, along with reviews of the 1st edition, errata, etc.
Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projects
Presents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods
Includes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface
Includes open-access online courses that introduce practical applications of the material in the book
Автор: Wei Lee Woon; Zeyar Aung; Oliver Kramer; Stuart Ma Название: Data Analytics for Renewable Energy Integration ISBN: 3319509462 ISBN-13(EAN): 9783319509464 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes revised selected papers from the 4th ECML PKDD Workshop on Data Analytics for Renewable Energy Integration, DARE 2016, held in Riva del Garda, Italy, in September 2016.
Автор: Wei Lee Woon; Zeyar Aung; Stuart Madnick Название: Data Analytics for Renewable Energy Integration ISBN: 3319274295 ISBN-13(EAN): 9783319274294 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This bookconstitutes revised selected papers from the third ECML PKDD Workshop on DataAnalytics for Renewable Energy Integration, DARE 2015, held in Porto, Portugal,in September 2015. The 10 papers presented in this volume were carefully reviewed and selected forinclusion in this book.
Автор: Christopher J.O. Baker; Greg Butler; Igor Jurisica Название: Data Integration in the Life Sciences ISBN: 3642394361 ISBN-13(EAN): 9783642394362 Издательство: Springer Рейтинг: Цена: 6429.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the refereed proceedings of the 9th International Conference on Data Integration in the Life Sciences, DILS 2013, held in Montreal, QC, Canada, in July 2013.
Автор: Carlos Coello Coello; Satchidananda Dehuri; Susmit Название: Swarm Intelligence for Multi-objective Problems in Data Mining ISBN: 3642036244 ISBN-13(EAN): 9783642036248 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining.
Автор: Carlos Coello Coello; Satchidananda Dehuri; Susmit Название: Swarm Intelligence for Multi-objective Problems in Data Mining ISBN: 3642260535 ISBN-13(EAN): 9783642260537 Издательство: Springer Рейтинг: Цена: 29209.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The purpose of this book is to collect contributions that are at the intersection of multi-objective optimization, swarm intelligence (specifically, particle swarm optimization and ant colony optimization) and data mining.
Описание: Data warehousing is an important topic that is of interest to both the industry and the knowledge engineering research communities. Both data mining and data warehousing technologies have similar objectives and can potentially benefit from each other’s methods to facilitate knowledge discovery.Improving Knowledge Discovery through the Integration of Data Mining Techniques provides insight concerning the integration of data mining and data warehousing for enhancing the knowledge discovery process. Decision makers, academicians, researchers, advanced-level students, technology developers, and business intelligence professionals will find this book useful in furthering their research exposure to relevant topics in knowledge discovery.
Автор: Azevedo & Filipe Santos Название: Integration Of Data Mining In Business Intelligence Systems ISBN: 1466664770 ISBN-13(EAN): 9781466664777 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 29106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries.Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.
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