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Predictive Data Mining Models, David L. Olson; Desheng Wu


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Цена: 11179.00р.
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Автор: David L. Olson; Desheng Wu
Название:  Predictive Data Mining Models
ISBN: 9789811396632
Издательство: Springer
Классификация:



ISBN-10: 9811396639
Обложка/Формат: Hardcover
Страницы: 125
Вес: 0.38 кг.
Дата издания: 2020
Серия: Computational Risk Management
Язык: English
Издание: 2nd ed. 2020
Иллюстрации: 70 illustrations, color; 4 illustrations, black and white; xi, 125 p. 74 illus., 70 illus. in color.
Размер: 234 x 156 x 10
Читательская аудитория: Professional & vocational
Основная тема: Business and Management
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание:
This book provides an overview of predictive methods demonstrated by open source software modeling with Rattle (R’) and WEKA. Knowledge management involves application of human knowledge (epistemology) with the technological advances of our current society (computer systems) and big data, both in terms of collecting data and in analyzing it. We see three types of analytic tools. Descriptive analytics focus on reports of what has happened. Predictive analytics extend statistical and/or artificial intelligence to provide forecasting capability. It also includes classification modeling. Prescriptive analytics applies quantitative models to optimize systems, or at least to identify improved systems. Data mining includes descriptive and predictive modeling. Operations research includes all three. This book focuses on prescriptive analytics.
The book seeks to provide simple explanations and demonstration of some descriptive tools. This second edition provides more examples of big data impact, updates the content on visualization, clarifies some points, and expands coverage of association rules and cluster analysis. Chapter 1 gives an overview in the context of knowledge management. Chapter 2 discusses some basic data types. Chapter 3 covers fundamentals time series modeling tools, and Chapter 4 provides demonstration of multiple regression modeling. Chapter 5 demonstrates regression tree modeling. Chapter 6 presents autoregressive/integrated/moving average models, as well as GARCH models. Chapter 7 covers the set of data mining tools used in classification, to include special variants support vector machines, random forests, and boosting.
Models are demonstrated using business related data. The style of the book is intended to be descriptive, seeking to explain how methods work, with some citations, but without deep scholarly reference. The data sets and software are all selected for widespread availability and access by any reader with computer links.

Дополнительное описание:
Chapter 1 Knowledge Management.- Chapter 2 Data Sets.- Chapter 3 Basic Forecasting ToolsChapter 3 Basic Forecasting Tools.- Chapter 4 Multiple Regression.- Chapter 5 Regression Tree Models.- Chapter 6 Autoregressive Models.- Chapter 7 GARCH Models.-



Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies

Автор: Kelleher John D., Macnamee Brian, D`Arcy Aoife
Название: Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies
ISBN: 0262029448 ISBN-13(EAN): 9780262029445
Издательство: MIT Press
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Цена: 13543.00 р.
Наличие на складе: Нет в наличии.

Описание:

A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context.

After discussing the trajectory from data to insight to decision, the book describes four approaches to machine learning: information-based learning, similarity-based learning, probability-based learning, and error-based learning. Each of these approaches is introduced by a nontechnical explanation of the underlying concept, followed by mathematical models and algorithms illustrated by detailed worked examples. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution. The book, informed by the authors' many years of teaching machine learning, and working on predictive data analytics projects, is suitable for use by undergraduates in computer science, engineering, mathematics, or statistics; by graduate students in disciplines with applications for predictive data analytics; and as a reference for professionals.

Data Mining and Predictive Analytics

Автор: Larose Daniel T
Название: Data Mining and Predictive Analytics
ISBN: 1118116194 ISBN-13(EAN): 9781118116197
Издательство: Wiley
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Цена: 18842.00 р.
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Описание: Learn methods of data analysis and their application to real-world data sets This updated second edition serves as an introduction to data mining methods and models, including association rules, clustering, neural networks, logistic regression, and multivariate analysis.

Predictive statistics

Автор: Clarke, Bertrand S. (university Of Nebraska, Lincoln) Clarke, Jennifer L. (university Of Nebraska, Lincoln)
Название: Predictive statistics
ISBN: 1107028280 ISBN-13(EAN): 9781107028289
Издательство: Cambridge Academ
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Цена: 12514.00 р.
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Описание: Aimed at statisticians and machine learners, this retooling of statistical theory asserts that high-quality prediction should be the guiding principle of modeling and learning from data, then shows how. The fully predictive approach to statistical problems outlined embraces traditional subfields and `black box` settings, with computed examples.

Data Mining: The Textbook

Автор: С.Aggarwal
Название: Data Mining: The Textbook
ISBN: 3319141414 ISBN-13(EAN): 9783319141411
Издательство: Springer
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Цена: 9781.00 р.
Наличие на складе: Поставка под заказ.

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, 4 ed.

Автор: Witten, Ian H.
Название: Data Mining. Practical Machine Learning Tools and Techniques, 4 ed.
ISBN: 0128042915 ISBN-13(EAN): 9780128042915
Издательство: Elsevier Science
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Цена: 9262.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

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
Predictive Analytics, Data Mining and Big Data

Автор: Finlay Steven
Название: Predictive Analytics, Data Mining and Big Data
ISBN: 1137379278 ISBN-13(EAN): 9781137379276
Издательство: Springer
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Цена: 5589.00 р.
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Описание: This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.

Data Mining and Predictive Analysis

Автор: Colleen McCue
Название: Data Mining and Predictive Analysis
ISBN: 0128002298 ISBN-13(EAN): 9780128002292
Издательство: Elsevier Science
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Цена: 9936.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Data Mining and Predictive Analysis: Intelligence Gathering and Crime Analysis, 2nd Edition, describes clearly and simply how crime clusters and other intelligence can be used to deploy security resources most effectively. Rather than being reactive,security agencies can anticipate and prevent crime through the appropriate application of data mining and the use of standard computer programs. Data Mining and Predictive Analysis offers a clear, practical starting point for professionals who need to use data mining inhomeland security, security analysis, and operational law enforcementsettings.This revised text highlights new and emerging technology, discusses the importance of analytic contextfor ensuring successful implementation of advanced analytics in the operational setting, and covers new analytic service delivery models that increase ease of use and access to high-end technology and analytic capabilities. The use of predictive analytics inintelligence and securityanalysis enables the development of meaningful, information based tactics, strategy, and policy decisions in the operational public safety and security environment.

Predictive Analytics, Data Mining and Big Data

Автор: S. Finlay
Название: Predictive Analytics, Data Mining and Big Data
ISBN: 1349478687 ISBN-13(EAN): 9781349478682
Издательство: Springer
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Цена: 4890.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This in-depth guide provides managers with a solid understanding of data and data trends, the opportunities that it can offer to businesses, and the dangers of these technologies. Written in an accessible style, Steven Finlay provides a contextual roadmap for developing solutions that deliver benefits to organizations.

Computing Predictive Analytics, Business Intelligence, and Economics

Название: Computing Predictive Analytics, Business Intelligence, and Economics
ISBN: 177188729X ISBN-13(EAN): 9781771887298
Издательство: Taylor&Francis
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Цена: 17762.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This volume brings together research and system designs that address the scientific basis and the practical systems design issues that support areas ranging from intelligent business interfaces and predictive analytics to economics modeling.

Machine Learning for Beginners 2019: The Ultimate Guide to Artificial Intelligence, Neural Networks, and Predictive Modelling (Data Mining Algorithms

Автор: Henderson Matt
Название: Machine Learning for Beginners 2019: The Ultimate Guide to Artificial Intelligence, Neural Networks, and Predictive Modelling (Data Mining Algorithms
ISBN: 1999177037 ISBN-13(EAN): 9781999177034
Издательство: Неизвестно
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Цена: 6205.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Want to predict what your customers want to buy without them having to tell you? Want to accurately forecast sales trends for your marketing team better than any employee could ever do? Then keep reading.


You've heard it before. The rise of artificial intelligence and how it will soon replace human beings and take away our jobs. What exactly is it capable of and how does this impact me? The real question you should be asking yourself is how can I use this to my advantage? How can I use machine learning to benefit my business and surpass my business goals? This book has the answer.

Designed for the tech novice, this book will break down the fundamentals of machine learning and what it truly means. You will learn to leverage neural networks, predictive modelling, and data mining algorithms, illustrated with real-world applications for finance, business and marketing.

Machine learning isn't just for scientists or engineers anymore. It's become accessible to anyone, and you can discover it's benefits for your business.

In Machine Learning for Beginners 2019, we will reveal:

✅ The fundamentals of machine learning.

✅ Each of the buzzwords defined

✅ 20 real-world applications of machine learning.

✅ How to predict when a customer is about to churn (and prevent it from happening).

✅ How to "upsell" to your customers and close more sales.

✅ How to deal with missing data or poor data.

✅ Where to find free datasets and libraries.

✅ Exactly which machine learning libraries you need.

✅ And much much more


I know you might be overwhelmed at this point, but I assure you this book has been designed for absolute beginners. Everything is in plain English. There is no code, so no coding experience is required. You won't walk away a machine learning god, but you will walk away with key strategies you can implement right away to improve your business.

���� If you are ready to start making big changes to your business, scroll up and click buy. ����

Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database

Автор: Jones Herbert
Название: Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database
ISBN: 1647483263 ISBN-13(EAN): 9781647483265
Издательство: Неизвестно
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Цена: 4137.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Data science has a huge impact on how companies conduct business, and those who don`t learn about this revolutionaryfield could be left behind. You see, data science will help you make better decisions, know what products and services to release, and how to provide better service to your customers.

Data Mining for Dummies

Автор: Brown Meta S.
Название: Data Mining for Dummies
ISBN: 1118893174 ISBN-13(EAN): 9781118893173
Издательство: Wiley
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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.


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