Agents and Data Mining Interaction, Longbing Cao; Yifeng Zeng; Bo An; Andreas L. Symeo
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: Churn prediction, recognition, and mitigation have become essential topics in various industries. As a means for forecasting and manageing risk, further research in this field can greatly assist companies in making informed decisions based on future possible scenarios.Developing Churn Models Using Data Mining Techniques and Social Network Analysis provides an in-depth analysis of attrition modeling relevant to business planning and management. Through its insightful and detailed explanation of best practices, tools, and theory surrounding churn prediction and the integration of analytics tools, this publication is especially relevant to managers, data specialists, business analysts, academicians, and upper-level students.
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: Brown Meta S. Название: Data Mining for Dummies ISBN: 1118893174 ISBN-13(EAN): 9781118893173 Издательство: Wiley Рейтинг: Цена: 5067.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Delve into your data for the key to success Data mining is quickly becoming integral to creating value and business momentum.
Автор: Lars Eld?n Название: Matrix Methods in Data Mining and Pattern Recognition ISBN: 0898716268 ISBN-13(EAN): 9780898716269 Издательство: Cambridge Academ Рейтинг: Цена: 9029.00 р. Наличие на складе: Поставка под заказ.
Описание: Several very powerful numerical linear algebra techniques are available for solving problems in data mining and pattern recognition. This application-oriented book describes how modern matrix methods can be used to solve these problems, gives an introduction to matrix theory and decompositions, and provides students with a set of tools that can be modified for a particular application. Part I gives a short introduction to a few application areas before presenting linear algebra concepts and matrix decompositions that students can use in problem-solving environments such as MATLAB. In Part II, linear algebra techniques are applied to data mining problems. Part III is a brief introduction to eigenvalue and singular value algorithms. The applications discussed include classification of handwritten digits, text mining, text summarization, pagerank computations related to the Google search engine, and face recognition. Exercises and computer assignments are available on a Web page that supplements the book.
Автор: Longbing Cao; A.E. Gorodetsky; Jiming Liu; Gerhard Название: Agents and Data Mining Interaction ISBN: 3642036023 ISBN-13(EAN): 9783642036026 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 4th International Workshop on Agents and Data Mining Interaction ADMI 2009 Budapest Hungary May 101. .
Автор: Longbing Cao; Yifeng Zeng; Andreas L. Symeonidis; Название: Agents and Data Mining Interaction ISBN: 3642551912 ISBN-13(EAN): 9783642551918 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed and revised selected papers from the 9th International Workshop on Agents and Data Mining Interaction, ADMI 2013, held in Saint Paul, MN, USA in May 2013.
Автор: Longbing Cao; Yifeng Zeng; Andreas L. Symeonidis; Название: Agents and Data Mining Interaction ISBN: 3642362877 ISBN-13(EAN): 9783642362873 Издательство: Springer Рейтинг: Цена: 6429.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes the thoroughly refereed post-workshop proceedings of the 8th International Workshop on Agents and Data Mining Interaction, ADMI 2012, held in Valencia, Spain, in June 2012. The papers are organized in topical sections on agents for data mining, data mining for agents, and agent mining applications.
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.
Annotating the TCD D-ANS Corpus - A Multimodal Multimedia Monolingual Biometric Corpus of Spoken Social Interaction.- Steps Towards More Natural Human-Machine Interaction via Audio-Visual Word Prominence Detection.- Improving Robustness Against Environmental Sounds for Directing Attention of Social Robots.- On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.- Modelling User Experience in Human-Robot Interactions.- Disposition Recognition from Spontaneous Speech Towards a Combination with Co-speech Gestures.- ASR Independent Hybrid Recurrent Neural Network Based Error Correction for Dialog System Applications.- Acquisition and Use of Long-Term Memory for Personalized Dialog Systems.- An Automatic Shout Detection System Using Speech Production Features.- Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose.- A Multimodal Multimedia Monolingual Biometric Corpus of Spoken Social Interaction.- Steps Towards More Natural Human-Machine Interaction via Audio-Visual Word Prominence Detection.- Improving Robustness Against Environmental Sounds for Directing Attention of Social Robots.- On Annotation and Evaluation of Multi-modal Corpora in Affective Human-Computer Interaction.- Modelling User Experience in Human-Robot Interactions.-Disposition Recognition from Spontaneous Speech Towards a Combination with Co-speech Gestures.- ASR Independent Hybrid Recurrent Neural Network Based Error Correction for Dialog System Applications.- Acquisition and Use of Long-Term Memory for Personalized Dialog Systems.- An Automatic Shout Detection System Using Speech Production Features.- Collecting Data for Automatic Speech Recognition Systems in Dialectal Arabic Using Games with a Purpose.
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
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