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Supervised and Unsupervised Ensemble Methods and their Applications

Supervised and Unsupervised Ensemble Methods and their Applications PDF Author: Oleg Okun
Publisher: Springer Science & Business Media
ISBN: 3540789804
Category : Computers
Languages : en
Pages : 182

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Book Description
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.

Supervised and Unsupervised Ensemble Methods and their Applications

Supervised and Unsupervised Ensemble Methods and their Applications PDF Author: Oleg Okun
Publisher: Springer Science & Business Media
ISBN: 3540789804
Category : Computers
Languages : en
Pages : 182

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Book Description
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.

Applications of Supervised and Unsupervised Ensemble Methods

Applications of Supervised and Unsupervised Ensemble Methods PDF Author: Oleg Okun
Publisher: Springer Science & Business Media
ISBN: 3642039987
Category : Computers
Languages : en
Pages : 268

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Book Description
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.

Ensembles in Machine Learning Applications

Ensembles in Machine Learning Applications PDF Author: Oleg Okun
Publisher: Springer
ISBN: 3642229107
Category : Technology & Engineering
Languages : en
Pages : 252

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Book Description
This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms – advanced machine learning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a group of algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instances in a dataset and after that all votes are combined together to produce the final class or cluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems. This book consists of 14 chapters, each of which can be read independently of the others. In addition to two previous SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/or programming code of the algorithms described in them. This was done in order to facilitate ensemble adoption in practice and to help to both researchers and engineers developing ensemble applications.

Ensembles in Machine Learning Applications

Ensembles in Machine Learning Applications PDF Author: Oleg Okun
Publisher: Springer Science & Business Media
ISBN: 3642229093
Category : Computers
Languages : en
Pages : 252

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Book Description
This book contains the extended papers presented at the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA) that was held in conjunction with the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010, Barcelona, Catalonia, Spain). As its two predecessors, its main theme was ensembles of supervised and unsupervised algorithms – advanced machine learning and data mining technique. Unlike a single classification or clustering algorithm, an ensemble is a group of algorithms, each of which first independently solves the task at hand by assigning a class or cluster label (voting) to instances in a dataset and after that all votes are combined together to produce the final class or cluster membership. As a result, ensembles often outperform best single algorithms in many real-world problems. This book consists of 14 chapters, each of which can be read independently of the others. In addition to two previous SUEMA editions, also published by Springer, many chapters in the current book include pseudo code and/or programming code of the algorithms described in them. This was done in order to facilitate ensemble adoption in practice and to help to both researchers and engineers developing ensemble applications.

Advances in Machine Learning and Data Mining for Astronomy

Advances in Machine Learning and Data Mining for Astronomy PDF Author: Michael J. Way
Publisher: CRC Press
ISBN: 143984173X
Category : Computers
Languages : en
Pages : 744

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Book Description
Advances in Machine Learning and Data Mining for Astronomy documents numerous successful collaborations among computer scientists, statisticians, and astronomers who illustrate the application of state-of-the-art machine learning and data mining techniques in astronomy. Due to the massive amount and complexity of data in most scientific disciplines, the material discussed in this text transcends traditional boundaries between various areas in the sciences and computer science. The book’s introductory part provides context to issues in the astronomical sciences that are also important to health, social, and physical sciences, particularly probabilistic and statistical aspects of classification and cluster analysis. The next part describes a number of astrophysics case studies that leverage a range of machine learning and data mining technologies. In the last part, developers of algorithms and practitioners of machine learning and data mining show how these tools and techniques are used in astronomical applications. With contributions from leading astronomers and computer scientists, this book is a practical guide to many of the most important developments in machine learning, data mining, and statistics. It explores how these advances can solve current and future problems in astronomy and looks at how they could lead to the creation of entirely new algorithms within the data mining community.

Design of Interpretable Fuzzy Systems

Design of Interpretable Fuzzy Systems PDF Author: Krzysztof Cpałka
Publisher: Springer
ISBN: 3319528815
Category : Technology & Engineering
Languages : en
Pages : 196

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Book Description
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.

Data Science and Innovations for Intelligent Systems

Data Science and Innovations for Intelligent Systems PDF Author: Kavita Taneja
Publisher: CRC Press
ISBN: 1000456153
Category : Technology & Engineering
Languages : en
Pages : 382

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Book Description
Data science is an emerging field and innovations in it need to be explored for the success of society 5.0. This book not only focuses on the practical applications of data science to achieve computational excellence, but also digs deep into the issues and implications of intelligent systems. This book highlights innovations in data science to achieve computational excellence that can optimize performance of smart applications. The book focuses on methodologies, framework, design issues, tools, architectures, and technologies necessary to develop and understand data science and its emerging applications in the present era. This book will be useful for the research community, start-up entrepreneurs, academicians, and data centered industries and professors that are interested in exploring innovations in varied applications and areas of data science.

Proceedings

Proceedings PDF Author:
Publisher: Presses universitaires de Louvain
ISBN: 2875870157
Category :
Languages : en
Pages : 601

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Book Description


Image Fusion

Image Fusion PDF Author: H.B. Mitchell
Publisher: Springer Science & Business Media
ISBN: 3642112161
Category : Technology & Engineering
Languages : en
Pages : 247

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Book Description
The purpose of this book is to provide a practical introduction to the th- ries, techniques and applications of image fusion. The present work has been designed as a textbook for a one-semester ?nal-year undergraduate, or ?r- year graduate, course in image fusion. It should also be useful to practising engineers who wish to learn the concepts of image fusion and apply them to practical applications. In addition, the book may also be used as a supp- mentary text for a graduate course on topics in advanced image processing. The book complements the author’s previous work on multi-sensor data [1] fusion by concentrating exclusively on the theories, techniques and app- cations of image fusion. The book is intended to be self-contained in so far as the subject of image fusion is concerned, although some prior exposure to the ?eld of computer vision and image processing may be helpful to the reader. Apart from two preliminary chapters, the book is divided into three parts.

Intelligent Science and Intelligent Data Engineering

Intelligent Science and Intelligent Data Engineering PDF Author: Jian Yang
Publisher: Springer
ISBN: 3642366694
Category : Computers
Languages : en
Pages : 880

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Book Description
This book constitutes the proceedings of the third Sino-foreign-interchange Workshop on Intelligence Science and Intelligent Data Engineering, IScIDE 2012, held in Nanjing, China, in October 2012. The 105 papers presented were carefully peer-reviewed and selected from 429 submissions. Topics covered include pattern recognition; computer vision and image processing; machine learning and computational intelligence; knowledge discovery, data mining, and web mining; graphics and computer visualization; and multimedia processing and applications.