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Active Mining, Shusaku Tsumoto; Takahira Yamaguchi; Masayuki Numa


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Цена: 69870.00T
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Склад Америка: 141 шт.  
При оформлении заказа до: 2025-09-29
Ориентировочная дата поставки: начало Ноября
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Автор: Shusaku Tsumoto; Takahira Yamaguchi; Masayuki Numa
Название:  Active Mining
ISBN: 9783540261575
Издательство: Springer
Классификация: ISBN-10: 3540261575
Обложка/Формат: Paperback
Страницы: 349
Вес: 0.52 кг.
Дата издания: 2005
Серия: Lecture Notes in Computer Science
Язык: English
Размер: 234 x 156 x 20
Читательская аудитория: Science
Ссылка на Издательство: Link
Поставляется из: Германии

Introductory Mining Engineering, 2nd Edition

Автор: Howard L. Hartman
Название: Introductory Mining Engineering, 2nd Edition
ISBN: 0471348511 ISBN-13(EAN): 9780471348511
Издательство: Wiley
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Цена: 157290.00 T
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Описание: Mining Engineering covers both above ground and underground methods for a wide variety of mineral substances, including metals, non-metals, and fuels. Completely revised, this book includes updated material on remote sensing, GPS, seismic surveying, ground-penetrating radar, continuous integrated mining operations, and autonomous trucks.

Data Science For Business: What You Need To Know About Data Mining And Dataanalytic Thinking

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
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Цена: 38010.00 T
Наличие на складе: Есть
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.

Developing Churn Models Using Data Mining Techniques And Social Network Analysis

Автор: Klepac, Kopal & Mrsic
Название: Developing Churn Models Using Data Mining Techniques And Social Network Analysis
ISBN: 1466662883 ISBN-13(EAN): 9781466662889
Издательство: Mare Nostrum (Eurospan)
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Цена: 180180.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
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.

Data Mining with Decision Trees

Автор: Lior Rokach
Название: Data Mining with Decision Trees
ISBN: 981459007X ISBN-13(EAN): 9789814590075
Издательство: World Scientific Publishing
Цена: 110880.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:

Decision trees have become one of the most powerful and popular approaches in knowledge discovery and data mining; it is the science of exploring large and complex bodies of data in order to discover useful patterns. Decision tree learning continues to evolve over time. Existing methods are constantly being improved and new methods introduced.

This 2nd Edition is dedicated entirely to the field of decision trees in data mining; to cover all aspects of this important technique, as well as improved or new methods and techniques developed after the publication of our first edition. In this new edition, all chapters have been revised and new topics brought in. New topics include Cost-Sensitive Active Learning, Learning with Uncertain and Imbalanced Data, Using Decision Trees beyond Classification Tasks, Privacy Preserving Decision Tree Learning, Lessons Learned from Comparative Studies, and Learning Decision Trees for Big Data. A walk-through guide to existing open-source data mining software is also included in this edition.

This book invites readers to explore the many benefits in data mining that decision trees offer:

  • Self-explanatory and easy to follow when compacted
  • Able to handle a variety of input data: nominal, numeric and textual
  • Scales well to big data
  • Able to process datasets that may have errors or missing values
  • High predictive performance for a relatively small computational effort
  • Available in many open source data mining packages over a variety of platforms
  • Useful for various tasks, such as classification, regression, clustering and feature selection

Data Mining: Concepts and Techniques,

Автор: Jiawei Han
Название: Data Mining: Concepts and Techniques,
ISBN: 0123814790 ISBN-13(EAN): 9780123814791
Издательство: Elsevier Science
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Цена: 64800.00 T
Наличие на складе: Нет в наличии.
Описание: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining.

Data Mining: Practical Machine Learning Tools and Techniques,

Автор: Ian H. Witten
Название: Data Mining: Practical Machine Learning Tools and Techniques,
ISBN: 0123748569 ISBN-13(EAN): 9780123748560
Издательство: Elsevier Science
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Цена: 57970.00 T
Наличие на складе: Нет в наличии.
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>

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: 65210.00 T
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.

Active Listening - Improve Your Ability to Listen and Lead??

Автор: Michael H. Hoppe
Название: Active Listening - Improve Your Ability to Listen and Lead??
ISBN: 1882197941 ISBN-13(EAN): 9781882197941
Издательство: Wiley
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Цена: 13720.00 T
Наличие на складе: Невозможна поставка.
Описание: Listening well is an essential component of good leadership. You can become a more effective listener and leader by learning the skills of active listening. Working relationships become more solid, based on trust, respect, and honesty. Active listening is not an optional component of leadership; it is not a nicety to be used to make others feel good. It is, in fact, a critical component of the tasks facing today's leaders.

Statistical and Machine-Learning Data Mining

Автор: Ratner Bruce
Название: Statistical and Machine-Learning Data Mining
ISBN: 1439860912 ISBN-13(EAN): 9781439860915
Издательство: Taylor&Francis
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Цена: 60220.00 T
Наличие на складе: Поставка под заказ.
Описание: Rev. ed. of: Statistical modeling and analysis for database marketing. c2003.

Teacher Education Through Active Engagement

Автор: Lori Beckett (Editor)
Название: Teacher Education Through Active Engagement
ISBN: 0415821681 ISBN-13(EAN): 9780415821681
Издательство: Taylor&Francis
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Цена: 158230.00 T
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Описание:

Teacher Education through Active Engagement identifies and addresses a contemporary issue: the ways in which teaching and teacher education are articulated by politicians, civil servants, business leaders and educational entrepreneurs intent on profit-making in the current global neoliberal policy context. This is often characterised by narrow and ill-conceived ideas about teacher characteristics and competences; recruiting and fast-tracking graduates from elsewhere into the profession; the reform of teacher training with less emphasis on theory and academic study; a narrow focus on teachers' core skills; and the promotion of training in model 'teaching schools'.

In this book contributors challenge this conceptualisation and demonstrate practitioners' necessary intellectual activity to wrest back professional control. By drawing on practice-focused research carried out in sites of educational policy and practice, each chapter exemplifies for teachers, student teachers and teacher educators the sort of 'knowledge work' to coordinate a professional reply to non-educationalists who dictate the terms of teaching and teacher education. The book provides directions for encouraging critical thinking, analytical skills and political activism, which consider the needs and interests of diverse children and young people in real classrooms, real schools and real communities.

Illustrated throughout with practice-focused research and drawing on the historical case of Winifred Mercier and her colleagues at the City of Leeds training college who challenged the establishment to leave a legacy of professional control, the book will appeal to practitioners, academics and researchers in the fields of teacher education and education studies.


Matrix Methods in Data Mining and Pattern Recognition

Автор: Lars Eld?n
Название: Matrix Methods in Data Mining and Pattern Recognition
ISBN: 0898716268 ISBN-13(EAN): 9780898716269
Издательство: Cambridge Academ
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Цена: 60190.00 T
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.

Data Mining with R

Автор: Torgo
Название: Data Mining with R
ISBN: 1439810184 ISBN-13(EAN): 9781439810187
Издательство: Taylor&Francis
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Цена: 66340.00 T
Наличие на складе: Поставка под заказ.
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.


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