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Multiple Classifier Systems

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Cover of 'Multiple Classifier Systems'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Bagging and the Random Subspace Method for Redundant Feature Spaces
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    Chapter 2 Performance Degradation in Boosting
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    Chapter 3 A Generalized Class of Boosting Algorithms Based on Recursive Decoding Models
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    Chapter 4 Tuning Cost-Sensitive Boosting and Its Application to Melanoma Diagnosis
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    Chapter 5 Learning Classification RBF Networks by Boosting
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    Chapter 6 Data Complexity Analysis for Classifier Combination
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    Chapter 7 Genetic Programming for Improved Receiver Operating Characteristics
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    Chapter 8 Methods for Designing Multiple Classifier Systems
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    Chapter 9 Decision-Level Fusion in Fingerprint Verification
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    Chapter 10 Genetic Algorithms for Multi-classifier System Configuration: A Case Study in Character Recognition
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    Chapter 11 Combined Classification of Handwritten Digits Using the ‘Virtual Test Sample Method’
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    Chapter 12 Averaging Weak Classifiers
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    Chapter 13 Mixing a Symbolic and a Subsymbolic Expert to Improve Carcinogenicity Prediction of Aromatic Compounds
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    Chapter 14 Multiple Classifier Systems Based on Interpretable Linear Classifiers
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    Chapter 15 Least Squares and Estimation Measures via Error Correcting Output Code
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    Chapter 16 Dependence among Codeword Bits Errors in ECOC Learning Machines: An Experimental Analysis
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    Chapter 17 Information Analysis of Multiple Classifier Fusion?
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    Chapter 18 Limiting the Number of Trees in Random Forests
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    Chapter 19 Learning-Data Selection Mechanism through Neural Networks Ensemble
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    Chapter 20 A Multi-SVM Classification System
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    Chapter 21 Automatic Classification of Clustered Microcalcifications by a Multiple Classifier System
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    Chapter 22 Feature Weighted Ensemble Classifiers – A Modified Decision Scheme
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    Chapter 23 Feature Subsets for Classifier Combination: An Enumerative Experiment
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    Chapter 24 Input Decimation Ensembles: Decorrelation through Dimensionality Reduction
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    Chapter 25 Classifier Combination as a Tomographic Process
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    Chapter 26 A Robust Multiple Classifier System for a Partially Unsupervised Updating of Land-Cover Maps
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    Chapter 27 Combining Supervised Remote Sensing Image Classifiers Based on Individual Class Performances
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    Chapter 28 Boosting, Bagging, and Consensus Based Classification of Multisource Remote Sensing Data
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    Chapter 29 Solar Wind Data Analysis Using Self-Organizing Hierarchical Neural Network Classifiers
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    Chapter 30 Combining One-Class Classifiers
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    Chapter 31 Finding Consistent Clusters in Data Partitions
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    Chapter 32 A Self-Organising Approach to Multiple Classifier Fusion
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    Chapter 33 Error Rejection in Linearly Combined Multiple Classifiers
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    Chapter 34 Relationship of Sum and Vote Fusion Strategies
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    Chapter 35 Complexity of Data Subsets Generated by the Random Subspace Method: An Experimental Investigation
  37. Altmetric Badge
    Chapter 36 On Combining Dissimilarity Representations
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    Chapter 37 Application of Multiple Classifier Techniques to Subband Speaker Identification with an HMM/ANN System
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    Chapter 38 Classification of Time Series Utilizing Temporal and Decision Fusion
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    Chapter 39 Use of Positional Information in Sequence Alignment for Multiple Classifier Combination
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    Chapter 40 Application of the Evolutionary Algorithms for Classifier Selection in Multiple Classifier Systems with Majority Voting
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    Chapter 41 Tree-Structured Support Vector Machines for Multi-class Pattern Recognition
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    Chapter 42 On the Combination of Different Template Matching Strategies for Fast Face Detection
  44. Altmetric Badge
    Chapter 43 Improving Product by Moderating k-NN Classifiers
  45. Altmetric Badge
    Chapter 44 Automatic Model Selection in a Hybrid Perceptron/Radial Network
Attention for Chapter 30: Combining One-Class Classifiers
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Chapter title
Combining One-Class Classifiers
Chapter number 30
Book title
Multiple Classifier Systems
Published by
Springer, Berlin, Heidelberg, July 2001
DOI 10.1007/3-540-48219-9_30
Book ISBNs
978-3-54-042284-6, 978-3-54-048219-2
Authors

David M. J. Tax, Robert P. W. Duin

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Belgium 2 2%
Spain 2 2%
Canada 1 1%
India 1 1%
United Kingdom 1 1%
United States 1 1%
Unknown 83 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 22%
Student > Ph. D. Student 19 21%
Student > Master 14 15%
Professor > Associate Professor 9 10%
Student > Doctoral Student 5 5%
Other 14 15%
Unknown 10 11%
Readers by discipline Count As %
Computer Science 43 47%
Engineering 13 14%
Physics and Astronomy 3 3%
Business, Management and Accounting 2 2%
Agricultural and Biological Sciences 2 2%
Other 11 12%
Unknown 17 19%