Author: Nikunj C. Oza
Publisher: Springer Science & Business Media
ISBN: 3540263063
Category : Computers
Languages : en
Pages : 440
Book Description
This book constitutes the refereed proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005, held in Seaside, CA, USA in June 2005. The 42 revised full papers presented were carefully reviewed and are organized in topical sections on boosting, combination methods, design of ensembles, performance analysis, and applications. They exemplify significant advances in the theory, algorithms, and applications of multiple classifier systems – bringing the different scientific communities together.
Multiple Classifier Systems
Author: Nikunj C. Oza
Publisher: Springer Science & Business Media
ISBN: 3540263063
Category : Computers
Languages : en
Pages : 440
Book Description
This book constitutes the refereed proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005, held in Seaside, CA, USA in June 2005. The 42 revised full papers presented were carefully reviewed and are organized in topical sections on boosting, combination methods, design of ensembles, performance analysis, and applications. They exemplify significant advances in the theory, algorithms, and applications of multiple classifier systems – bringing the different scientific communities together.
Publisher: Springer Science & Business Media
ISBN: 3540263063
Category : Computers
Languages : en
Pages : 440
Book Description
This book constitutes the refereed proceedings of the 6th International Workshop on Multiple Classifier Systems, MCS 2005, held in Seaside, CA, USA in June 2005. The 42 revised full papers presented were carefully reviewed and are organized in topical sections on boosting, combination methods, design of ensembles, performance analysis, and applications. They exemplify significant advances in the theory, algorithms, and applications of multiple classifier systems – bringing the different scientific communities together.
Multiple Classifier Systems
Author: Fabio Roli
Publisher: Springer
ISBN: 3540454284
Category : Computers
Languages : en
Pages : 347
Book Description
This book constitutes the refereed proceedings of the Third International Workshop on Multiple Classifier Systems, MCS 2002, held in Cagliari, Italy, in June 2002.The 29 revised full papers presented together with three invited papers were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on bagging and boosting, ensemble learning and neural networks, design methodologies, combination strategies, analysis and performance evaluation, and applications.
Publisher: Springer
ISBN: 3540454284
Category : Computers
Languages : en
Pages : 347
Book Description
This book constitutes the refereed proceedings of the Third International Workshop on Multiple Classifier Systems, MCS 2002, held in Cagliari, Italy, in June 2002.The 29 revised full papers presented together with three invited papers were carefully reviewed and selected for inclusion in the volume. The papers are organized in topical sections on bagging and boosting, ensemble learning and neural networks, design methodologies, combination strategies, analysis and performance evaluation, and applications.
Ensemble Classification Methods with Applications in R
Author: Esteban Alfaro
Publisher: John Wiley & Sons
ISBN: 1119421098
Category : Mathematics
Languages : en
Pages : 174
Book Description
An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts and principles of ensemble classifiers methods and includes a review of the most commonly used techniques. This important resource shows how ensemble classification has become an extension of the individual classifiers. The text puts the emphasis on two areas of machine learning: classification trees and ensemble learning. The authors explore ensemble classification methods’ basic characteristics and explain the types of problems that can emerge in its application. Written by a team of noted experts in the field, the text is divided into two main sections. The first section outlines the theoretical underpinnings of the topic and the second section is designed to include examples of practical applications. The book contains a wealth of illustrative cases of business failure prediction, zoology, ecology and others. This vital guide: Offers an important text that has been tested both in the classroom and at tutorials at conferences Contains authoritative information written by leading experts in the field Presents a comprehensive text that can be applied to courses in machine learning, data mining and artificial intelligence Combines in one volume two of the most intriguing topics in machine learning: ensemble learning and classification trees Written for researchers from many fields such as biostatistics, economics, environment, zoology, as well as students of data mining and machine learning, Ensemble Classification Methods with Applications in R puts the focus on two topics in machine learning: classification trees and ensemble learning.
Publisher: John Wiley & Sons
ISBN: 1119421098
Category : Mathematics
Languages : en
Pages : 174
Book Description
An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts and principles of ensemble classifiers methods and includes a review of the most commonly used techniques. This important resource shows how ensemble classification has become an extension of the individual classifiers. The text puts the emphasis on two areas of machine learning: classification trees and ensemble learning. The authors explore ensemble classification methods’ basic characteristics and explain the types of problems that can emerge in its application. Written by a team of noted experts in the field, the text is divided into two main sections. The first section outlines the theoretical underpinnings of the topic and the second section is designed to include examples of practical applications. The book contains a wealth of illustrative cases of business failure prediction, zoology, ecology and others. This vital guide: Offers an important text that has been tested both in the classroom and at tutorials at conferences Contains authoritative information written by leading experts in the field Presents a comprehensive text that can be applied to courses in machine learning, data mining and artificial intelligence Combines in one volume two of the most intriguing topics in machine learning: ensemble learning and classification trees Written for researchers from many fields such as biostatistics, economics, environment, zoology, as well as students of data mining and machine learning, Ensemble Classification Methods with Applications in R puts the focus on two topics in machine learning: classification trees and ensemble learning.
Multiple Classifier Systems
Author: Carlo Sansone
Publisher: Springer Science & Business Media
ISBN: 3642215564
Category : Computers
Languages : en
Pages : 382
Book Description
This book constitutes the refereed proceedings of the 10th International Workshop on Multiple Classifier Systems, MCS 2011, held in Naples, Italy, in June 2011. The 36 revised papers presented together with two invited papers were carefully reviewed and selected from more than 50 submissions. The contributions are organized into sessions dealing with classifier ensembles; trees and forests; one-class classifiers; multiple kernels; classifier selection; sequential combination; ECOC; diversity; clustering; biometrics; and computer security.
Publisher: Springer Science & Business Media
ISBN: 3642215564
Category : Computers
Languages : en
Pages : 382
Book Description
This book constitutes the refereed proceedings of the 10th International Workshop on Multiple Classifier Systems, MCS 2011, held in Naples, Italy, in June 2011. The 36 revised papers presented together with two invited papers were carefully reviewed and selected from more than 50 submissions. The contributions are organized into sessions dealing with classifier ensembles; trees and forests; one-class classifiers; multiple kernels; classifier selection; sequential combination; ECOC; diversity; clustering; biometrics; and computer security.
Hybrid Methods in Pattern Recognition
Author: Horst Bunke
Publisher: World Scientific Publishing Company Incorporated
ISBN: 9789810248321
Category : Computers
Languages : en
Pages : 324
Book Description
The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and subsymbolic learning, and so on. Also included is recent work on multiple classifier systems. Furthermore, the book deals with applications in on-line and off-line handwriting recognition, remotely sensed image interpretation, fingerprint identification, and automatic text categorization.
Publisher: World Scientific Publishing Company Incorporated
ISBN: 9789810248321
Category : Computers
Languages : en
Pages : 324
Book Description
The field of pattern recognition has seen enormous progress since its beginnings almost 50 years ago. A large number of different approaches have been proposed. Hybrid methods aim at combining the advantages of different paradigms within a single system. Hybrid Methods in Pattern Recognition is a collection of articles describing recent progress in this emerging field. It covers topics such as the combination of neural nets with fuzzy systems or hidden Markov models, neural networks for the processing of symbolic data structures, hybrid methods in data mining, the combination of symbolic and subsymbolic learning, and so on. Also included is recent work on multiple classifier systems. Furthermore, the book deals with applications in on-line and off-line handwriting recognition, remotely sensed image interpretation, fingerprint identification, and automatic text categorization.
Multiple Classifier Systems
Author: Jón Atli Benediktsson
Publisher: Springer Science & Business Media
ISBN: 3642023258
Category : Computers
Languages : en
Pages : 551
Book Description
This book constitutes the refereed proceedings of the 8th International Workshop on Multiple Classifier Systems, MCS 2009, held in Reykjavik, Iceland, in June 2009. The 52 revised full papers presented together with 2 invited papers were carefully reviewed and selected from more than 70 initial submissions. The papers are organized in topical sections on ECOC boosting and bagging, MCS in remote sensing, unbalanced data and decision templates, stacked generalization and active learning, concept drift, missing values and random forest, SVM ensembles, fusion of graphics, concepts and categorical data, clustering, and finally theory, methods and applications of MCS.
Publisher: Springer Science & Business Media
ISBN: 3642023258
Category : Computers
Languages : en
Pages : 551
Book Description
This book constitutes the refereed proceedings of the 8th International Workshop on Multiple Classifier Systems, MCS 2009, held in Reykjavik, Iceland, in June 2009. The 52 revised full papers presented together with 2 invited papers were carefully reviewed and selected from more than 70 initial submissions. The papers are organized in topical sections on ECOC boosting and bagging, MCS in remote sensing, unbalanced data and decision templates, stacked generalization and active learning, concept drift, missing values and random forest, SVM ensembles, fusion of graphics, concepts and categorical data, clustering, and finally theory, methods and applications of MCS.
Multiple Classifier Systems
Author: Josef Kittler
Publisher: Springer
ISBN: 3540482199
Category : Computers
Languages : en
Pages : 468
Book Description
Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule. This observation has motivated the recent interest in Multiple Classi er Systems , which aim to make use of several designs jointly to obtain a better estimate of the optimal decision boundary and thus improve the system performance. This volume contains the proceedings of the international workshop on Multiple Classi er Systems held at Robinson College, Cambridge, United Kingdom (July 2{4, 2001), which was organized to provide a forum for researchers in this subject area to exchange views and report their latest results.
Publisher: Springer
ISBN: 3540482199
Category : Computers
Languages : en
Pages : 468
Book Description
Driven by the requirements of a large number of practical and commercially - portant applications, the last decade has witnessed considerable advances in p- tern recognition. Better understanding of the design issues and new paradigms, such as the Support Vector Machine, have contributed to the development of - proved methods of pattern classi cation. However, while any performance gains are welcome, and often extremely signi cant from the practical point of view, it is increasingly more challenging to reach the point of perfection as de ned by the theoretical optimality of decision making in a given decision framework. The asymptoticity of gains that can be made for a single classi er is a re?- tion of the fact that any particular design, regardless of how good it is, simply provides just one estimate of the optimal decision rule. This observation has motivated the recent interest in Multiple Classi er Systems , which aim to make use of several designs jointly to obtain a better estimate of the optimal decision boundary and thus improve the system performance. This volume contains the proceedings of the international workshop on Multiple Classi er Systems held at Robinson College, Cambridge, United Kingdom (July 2{4, 2001), which was organized to provide a forum for researchers in this subject area to exchange views and report their latest results.
A Grammar of Murui (Bue)
Author: Katarzyna I. Wojtylak
Publisher: BRILL
ISBN: 9004432671
Category : Language Arts & Disciplines
Languages : en
Pages : 613
Book Description
A Grammar of Murui (Bue) by Katarzyna Wojtylak is the first complete description of Murui (Witoto, Huitoto) spoken in Colombia and Peru. It is an important contribution to the study of Witotoan languages and linguistic typology of Northwest Amazonia.
Publisher: BRILL
ISBN: 9004432671
Category : Language Arts & Disciplines
Languages : en
Pages : 613
Book Description
A Grammar of Murui (Bue) by Katarzyna Wojtylak is the first complete description of Murui (Witoto, Huitoto) spoken in Colombia and Peru. It is an important contribution to the study of Witotoan languages and linguistic typology of Northwest Amazonia.
Combining Artificial Neural Nets
Author: Amanda J.C. Sharkey
Publisher: Springer Science & Business Media
ISBN: 1447107934
Category : Computers
Languages : en
Pages : 300
Book Description
This volume, written by leading researchers, presents methods of combining neural nets to improve their performance. The techniques include ensemble-based approaches, where a variety of methods are used to create a set of different nets trained on the same task, and modular approaches, where a task is decomposed into simpler problems. The techniques are also accompanied by an evaluation of their relative effectiveness and their application to a variety of problems.
Publisher: Springer Science & Business Media
ISBN: 1447107934
Category : Computers
Languages : en
Pages : 300
Book Description
This volume, written by leading researchers, presents methods of combining neural nets to improve their performance. The techniques include ensemble-based approaches, where a variety of methods are used to create a set of different nets trained on the same task, and modular approaches, where a task is decomposed into simpler problems. The techniques are also accompanied by an evaluation of their relative effectiveness and their application to a variety of problems.
Multiple Classifier Systems
Author: Fabio Roli
Publisher: Springer
ISBN: 9783662202890
Category : Computers
Languages : en
Pages : 392
Book Description
The fusion of di?erent information sourcesis a persistent and intriguing issue. It hasbeenaddressedforcenturiesinvariousdisciplines,includingpoliticalscience, probability and statistics, system reliability assessment, computer science, and distributed detection in communications. Early seminal work on fusion was c- ried out by pioneers such as Laplace and von Neumann. More recently, research activities in information fusion have focused on pattern recognition. During the 1990s,classi?erfusionschemes,especiallyattheso-calleddecision-level,emerged under a plethora of di?erent names in various scienti?c communities, including machine learning, neural networks, pattern recognition, and statistics. The d- ferent nomenclatures introduced by these communities re?ected their di?erent perspectives and cultural backgrounds as well as the absence of common forums and the poor dissemination of the most important results. In 1999, the ?rst workshop on multiple classi?er systems was organized with the main goal of creating a common international forum to promote the diss- ination of the results achieved in the diverse communities and the adoption of a common terminology, thus giving the di?erent perspectives and cultural ba- grounds some concrete added value. After ?ve meetings of this workshop, there is strong evidence that signi?cant steps have been made towards this goal. - searchers from these diverse communities successfully participated in the wo- shops, and world experts presented surveys of the state of the art from the perspectives of their communities to aid cross-fertilization.
Publisher: Springer
ISBN: 9783662202890
Category : Computers
Languages : en
Pages : 392
Book Description
The fusion of di?erent information sourcesis a persistent and intriguing issue. It hasbeenaddressedforcenturiesinvariousdisciplines,includingpoliticalscience, probability and statistics, system reliability assessment, computer science, and distributed detection in communications. Early seminal work on fusion was c- ried out by pioneers such as Laplace and von Neumann. More recently, research activities in information fusion have focused on pattern recognition. During the 1990s,classi?erfusionschemes,especiallyattheso-calleddecision-level,emerged under a plethora of di?erent names in various scienti?c communities, including machine learning, neural networks, pattern recognition, and statistics. The d- ferent nomenclatures introduced by these communities re?ected their di?erent perspectives and cultural backgrounds as well as the absence of common forums and the poor dissemination of the most important results. In 1999, the ?rst workshop on multiple classi?er systems was organized with the main goal of creating a common international forum to promote the diss- ination of the results achieved in the diverse communities and the adoption of a common terminology, thus giving the di?erent perspectives and cultural ba- grounds some concrete added value. After ?ve meetings of this workshop, there is strong evidence that signi?cant steps have been made towards this goal. - searchers from these diverse communities successfully participated in the wo- shops, and world experts presented surveys of the state of the art from the perspectives of their communities to aid cross-fertilization.