Applications Of Supervised And Unsupervised Ensemble Methods
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Applications Of Supervised And Unsupervised Ensemble Methods
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Author : Oleg Okun
language : en
Publisher: Springer Science & Business Media
Release Date : 2009-10-06
Applications Of Supervised And Unsupervised Ensemble Methods written by Oleg Okun and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-06 with Computers categories.
Expanding upon presentations at last year’s SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent developments in the field. Useful examples act as a guide for practitioners in computational intelligence.
Applications Of Supervised And Unsupervised Ensemble Methods
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Author : Oleg Okun
language : en
Publisher: Springer
Release Date : 2009-10-15
Applications Of Supervised And Unsupervised Ensemble Methods written by Oleg Okun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-10-15 with Computers categories.
Expanding upon presentations at last year’s SUEMA (Supervised and Unsupervised Ensemble Methods and Applications) meeting, this volume explores recent developments in the field. Useful examples act as a guide for practitioners in computational intelligence.
Supervised And Unsupervised Ensemble Methods And Their Applications
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Author : Oleg Okun
language : en
Publisher: Springer
Release Date : 2008-04-20
Supervised And Unsupervised Ensemble Methods And Their Applications written by Oleg Okun and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-20 with Computers categories.
This book results from the workshop on Supervised and Unsupervised Ensemble Methods and their Applications (briefly, SUEMA) in June 2007 in Girona, Spain. This workshop was held alongside the 3rd Iberian Conference on Pattern Recognition and Image Analysis.
Ensemble Machine Learning
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Author : Cha Zhang
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-17
Ensemble Machine Learning written by Cha Zhang and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-17 with Computers categories.
It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.
Ensemble Methods
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Author : Zhi-Hua Zhou
language : en
Publisher: CRC Press
Release Date : 2012-06-06
Ensemble Methods written by Zhi-Hua Zhou and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-06 with Business & Economics categories.
An up-to-date, self-contained introduction to a state-of-the-art machine learning approach, Ensemble Methods: Foundations and Algorithms shows how these accurate methods are used in real-world tasks. It gives you the necessary groundwork to carry out further research in this evolving field. After presenting background and terminology, the book covers the main algorithms and theories, including Boosting, Bagging, Random Forest, averaging and voting schemes, the Stacking method, mixture of experts, and diversity measures. It also discusses multiclass extension, noise tolerance, error-ambiguity and bias-variance decompositions, and recent progress in information theoretic diversity. Moving on to more advanced topics, the author explains how to achieve better performance through ensemble pruning and how to generate better clustering results by combining multiple clusterings. In addition, he describes developments of ensemble methods in semi-supervised learning, active learning, cost-sensitive learning, class-imbalance learning, and comprehensibility enhancement.
Ensemble Methods
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Author : Zhi-Hua Zhou
language : en
Publisher: CRC Press
Release Date : 2025-02-15
Ensemble Methods written by Zhi-Hua Zhou and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-15 with Business & Economics categories.
Ensemble methods that train multiple learners and then combine them to use, with Boosting and Bagging as representatives, are well-known machine learning approaches. It has become common sense that an ensemble is usually significantly more accurate than a single learner, and ensemble methods have already achieved great success in various real-world tasks. Twelve years have passed since the publication of the first edition of the book in 2012 (Japanese and Chinese versions published in 2017 and 2020, respectively). Many significant advances in this field have been developed. First, many theoretical issues have been tackled, for example, the fundamental question of why AdaBoost seems resistant to overfitting gets addressed, so that now we understand much more about the essence of ensemble methods. Second, ensemble methods have been well developed in more machine learning fields, e.g., isolation forest in anomaly detection, so that now we have powerful ensemble methods for tasks beyond conventional supervised learning. Third, ensemble mechanisms have also been found helpful in emerging areas such as deep learning and online learning. This edition expands on the previous one with additional content to reflect the significant advances in the field, and is written in a concise but comprehensive style to be approachable to readers new to the subject.
Recent Advances In Ensembles For Feature Selection
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Author : Verónica Bolón-Canedo
language : en
Publisher: Springer
Release Date : 2018-04-30
Recent Advances In Ensembles For Feature Selection written by Verónica Bolón-Canedo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-04-30 with Technology & Engineering categories.
This book offers a comprehensive overview of ensemble learning in the field of feature selection (FS), which consists of combining the output of multiple methods to obtain better results than any single method. It reviews various techniques for combining partial results, measuring diversity and evaluating ensemble performance. With the advent of Big Data, feature selection (FS) has become more necessary than ever to achieve dimensionality reduction. With so many methods available, it is difficult to choose the most appropriate one for a given setting, thus making the ensemble paradigm an interesting alternative. The authors first focus on the foundations of ensemble learning and classical approaches, before diving into the specific aspects of ensembles for FS, such as combining partial results, measuring diversity and evaluating ensemble performance. Lastly, the book shows examples of successful applications of ensembles for FS and introduces the new challenges that researchers now face. As such, the book offers a valuable guide for all practitioners, researchers and graduate students in the areas of machine learning and data mining.
7th International Conference On Knowledge Management In Organizations Service And Cloud Computing
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Author : Lorna Uden
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-07-18
7th International Conference On Knowledge Management In Organizations Service And Cloud Computing written by Lorna Uden and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-18 with Technology & Engineering categories.
The seventh International Conference on Knowledge Management in Organizations (KMO) brings together researchers and developers from industry and the academic world to report on the latest scientific and technical advances on knowledge management in organisations. KMO 2012 provides an international forum for authors to present and discuss research focused on the role of knowledge management for innovative services in industries, to shed light on recent advances in cloud computing for KM as well as to identify future directions for researching the role of knowledge management in service innovation and how cloud computing can be used to address many of the issues currently facing KM in academia and industrial sectors. The conference took place at Salamanca in Spain on the 11th-13th July in 2012.
Fuzzy Logic And Applications
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Author : Robert Fullér
language : en
Publisher: Springer
Release Date : 2019-02-22
Fuzzy Logic And Applications written by Robert Fullér and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-22 with Computers categories.
This book constitutes the post-conference proceedings of the 12th International Workshop on Fuzzy Logic and Applications, WILF 2018, held in Genoa, Italy, in September 2018. The 17 revised full papers and 9 short papers were carefully reviewed and selected from 26 submissions. The papers are organized in topical sections on fuzzy logic theory, recent applications of fuzzy logic, and fuzzy decision making. Also included are papers from the round table "Zadeh and the future of logic" and a tutorial.
Design Of Interpretable Fuzzy Systems
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Author : Krzysztof Cpałka
language : en
Publisher: Springer
Release Date : 2017-01-31
Design Of Interpretable Fuzzy Systems written by Krzysztof Cpałka and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-31 with Technology & Engineering categories.
This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.