Encyclopedia Of Machine Learning And Data Mining

Author : Wang, John
Publisher : IGI Global
Page : 3296 pages
File Size : 55,5 Mb
Release : 2023-01-20
Category : Computers
ISBN : 9781799892212

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Encyclopedia of Data Science and Machine Learning by Wang, John Pdf

Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.

Author : Claude Sammut,Geoffrey I. Webb
Publisher : Springer Science & Business Media
Page : 1061 pages
File Size : 55,8 Mb
Release : 2011-03-28
Category : Computers
ISBN : 9780387307688

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Encyclopedia of Machine Learning by Claude Sammut,Geoffrey I. Webb Pdf

This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Author : Claude Sammut,Geoffrey I. Webb
Publisher : Springer
Page : 0 pages
File Size : 42,9 Mb
Release : 2017-03-15
Category : Computers
ISBN : 148997685X

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Encyclopedia of Machine Learning and Data Mining by Claude Sammut,Geoffrey I. Webb Pdf

This authoritative, expanded and updated second edition of Encyclopedia of Machine Learning and Data Mining provides easy access to core information for those seeking entry into any aspect within the broad field of Machine Learning and Data Mining. A paramount work, its 800 entries - about 150 of them newly updated or added - are filled with valuable literature references, providing the reader with a portal to more detailed information on any given topic.Topics for the Encyclopedia of Machine Learning and Data Mining include Learning and Logic, Data Mining, Applications, Text Mining, Statistical Learning, Reinforcement Learning, Pattern Mining, Graph Mining, Relational Mining, Evolutionary Computation, Information Theory, Behavior Cloning, and many others. Topics were selected by a distinguished international advisory board. Each peer-reviewed, highly-structured entry includes a definition, key words, an illustration, applications, a bibliography, and links to related literature.The entries are expository and tutorial, making this reference a practical resource for students, academics, or professionals who employ machine learning and data mining methods in their projects. Machine learning and data mining techniques have countless applications, including data science applications, and this reference is essential for anyone seeking quick access to vital information on the topic.

Author : Claude Sammut,Geoffrey I. Webb
Publisher : Unknown
Page : 128 pages
File Size : 54,8 Mb
Release : 2024-05-29
Category : Machine learning
ISBN : 1489975020

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Encyclopedia of Machine Learning and Data Mining by Claude Sammut,Geoffrey I. Webb Pdf

Author : Wang, John
Publisher : IGI Global
Page : 2542 pages
File Size : 45,6 Mb
Release : 2008-08-31
Category : Computers
ISBN : 9781605660110

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Encyclopedia of Data Warehousing and Mining, Second Edition by Wang, John Pdf

There are more than one billion documents on the Web, with the count continually rising at a pace of over one million new documents per day. As information increases, the motivation and interest in data warehousing and mining research and practice remains high in organizational interest. The Encyclopedia of Data Warehousing and Mining, Second Edition, offers thorough exposure to the issues of importance in the rapidly changing field of data warehousing and mining. This essential reference source informs decision makers, problem solvers, and data mining specialists in business, academia, government, and other settings with over 300 entries on theories, methodologies, functionalities, and applications.

Author : Igor Kononenko,Matjaz Kukar
Publisher : Elsevier
Page : 480 pages
File Size : 48,5 Mb
Release : 2007-04-30
Category : Computers
ISBN : 9780857099440

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Machine Learning and Data Mining by Igor Kononenko,Matjaz Kukar Pdf

Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining. Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining A valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions

Author : John Wang
Publisher : Encyclopedia of Data Science and Machine Learning
Page : 0 pages
File Size : 53,6 Mb
Release : 2022-10-14
Category : Electronic
ISBN : 1668481618

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Encyclopedia of Data Science and Machine Learning, VOL 1 by John Wang Pdf

Author : Claude Sammut,Geoffrey I. Webb
Publisher : Springer
Page : 1031 pages
File Size : 50,6 Mb
Release : 2010-11-12
Category : Computers
ISBN : 0387345582

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Encyclopedia of Machine Learning by Claude Sammut,Geoffrey I. Webb Pdf

This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Author : Xin-She Yang
Publisher : Academic Press
Page : 188 pages
File Size : 53,6 Mb
Release : 2019-07-15
Category : Mathematics
ISBN : 9780128172162

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Introduction to Algorithms for Data Mining and Machine Learning by Xin-She Yang Pdf

Introduction to Algorithms for Data Mining and Machine Learning introduces the essential ideas behind all key algorithms and techniques for data mining and machine learning, along with optimization techniques. Its strong formal mathematical approach, well selected examples, and practical software recommendations help readers develop confidence in their data modeling skills so they can process and interpret data for classification, clustering, curve-fitting and predictions. Masterfully balancing theory and practice, it is especially useful for those who need relevant, well explained, but not rigorous (proofs based) background theory and clear guidelines for working with big data. Presents an informal, theorem-free approach with concise, compact coverage of all fundamental topics Includes worked examples that help users increase confidence in their understanding of key algorithms, thus encouraging self-study Provides algorithms and techniques that can be implemented in any programming language, with each chapter including notes about relevant software packages

Author : Comandé, Giovanni
Publisher : Edward Elgar Publishing
Page : 400 pages
File Size : 48,5 Mb
Release : 2022-02-18
Category : Law
ISBN : 9781839104596

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Elgar Encyclopedia of Law and Data Science by Comandé, Giovanni Pdf

This Encyclopedia brings together jurists, computer scientists, and data analysts to map the emerging field of data science and law for the first time, uncovering the challenges, opportunities, and fault lines that arise as these groups are increasingly thrown together by expanding attempts to regulate and adapt to a data-driven world. It explains the concepts and tools at the crossroads of the many disciplines involved in data science and law, bridging scientific and applied domains. Entries span algorithmic fairness, consent, data protection, ethics, healthcare, machine learning, patents, surveillance, transparency and vulnerability.

Author : Lior Rokach,Oded Maimon,Erez Shmueli
Publisher : Springer Nature
Page : 975 pages
File Size : 48,6 Mb
Release : 2023-08-17
Category : Computers
ISBN : 9783031246289

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Machine Learning for Data Science Handbook by Lior Rokach,Oded Maimon,Erez Shmueli Pdf

This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.

Author : Pavel Brazdil,Christophe Giraud Carrier,Carlos Soares,Ricardo Vilalta
Publisher : Springer Science & Business Media
Page : 182 pages
File Size : 51,7 Mb
Release : 2008-11-26
Category : Computers
ISBN : 9783540732624

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Metalearning by Pavel Brazdil,Christophe Giraud Carrier,Carlos Soares,Ricardo Vilalta Pdf

Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.

Author : John Wang
Publisher : IGI Global Snippet
Page : 684 pages
File Size : 47,7 Mb
Release : 2009
Category : Business & Economics
ISBN : IND:30000115606075

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Encyclopedia of Data Warehousing and Mining by John Wang Pdf

"This set offers thorough examination of the issues of importance in the rapidly changing field of data warehousing and mining"--Provided by publisher.

Author : Rohit Raja,Kapil Kumar Nagwanshi,Sandeep Kumar,K. Ramya Laxmi
Publisher : John Wiley & Sons
Page : 500 pages
File Size : 45,9 Mb
Release : 2022-01-26
Category : Computers
ISBN : 9781119792505

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Data Mining and Machine Learning Applications by Rohit Raja,Kapil Kumar Nagwanshi,Sandeep Kumar,K. Ramya Laxmi Pdf

DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.

Author : Albert Bifet,Ricard Gavalda,Geoffrey Holmes,Bernhard Pfahringer
Publisher : MIT Press
Page : 289 pages
File Size : 50,8 Mb
Release : 2023-05-09
Category : Computers
ISBN : 9780262547833

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Machine Learning for Data Streams by Albert Bifet,Ricard Gavalda,Geoffrey Holmes,Bernhard Pfahringer Pdf

A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.