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Multiple Classifier Systems

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Cover of 'Multiple Classifier Systems'

Table of Contents

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    Book Overview
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    Chapter 1 A Novel Bagging Ensemble Approach for Variable Ranking and Selection for Linear Regression Models
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    Chapter 2 A Hierarchical Ensemble Method for DAG-Structured Taxonomies
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    Chapter 3 Diversity Measures and Margin Criteria in Multi-class Majority Vote Ensemble
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    Chapter 4 Fractional Programming Weighted Decoding for Error-Correcting Output Codes
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    Chapter 5 Instance-Based Decompositions of Error Correcting Output Codes
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    Chapter 6 Pruning Bagging Ensembles with Metalearning
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    Chapter 7 Multi-label Selective Ensemble
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    Chapter 8 Supervised Selective Combination of Diverse Object-Representation Modalities for Regression Estimation
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    Chapter 9 Detecting Ordinal Class Structures
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    Chapter 10 Multiple Classifier Systems
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    Chapter 11 Building Classifier Ensembles Using Greedy Graph Edit Distance
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    Chapter 12 Multiple Classifier Systems
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    Chapter 13 Suboptimal Graph Edit Distance Based on Sorted Local Assignments
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    Chapter 14 Multimodal PLSA for Movie Genre Classification
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    Chapter 15 One-and-a-Half-Class Multiple Classifier Systems for Secure Learning Against Evasion Attacks at Test Time
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    Chapter 16 An Experimental Study on Combining Binarization Techniques and Ensemble Methods of Decision Trees
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    Chapter 17 Decision Tree-Based Multiple Classifier Systems: An FPGA Perspective
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    Chapter 18 An Empirical Investigation on the Use of Diversity for Creation of Classifier Ensembles
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    Chapter 19 Bio-Visual Fusion for Person-Independent Recognition of Pain Intensity
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32 Mendeley
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Title
Multiple Classifier Systems
Published by
Springer International Publishing, June 2015
DOI 10.1007/978-3-319-20248-8
ISBNs
978-3-31-920247-1, 978-3-31-920248-8
Editors

Schwenker, Friedhelm, Roli, Fabio, Kittler, Josef

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 32 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 22%
Student > Bachelor 4 13%
Student > Doctoral Student 3 9%
Researcher 3 9%
Professor > Associate Professor 2 6%
Other 1 3%
Unknown 12 38%
Readers by discipline Count As %
Computer Science 12 38%
Engineering 3 9%
Agricultural and Biological Sciences 1 3%
Mathematics 1 3%
Social Sciences 1 3%
Other 1 3%
Unknown 13 41%