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Multiple Classifier Systems

Overview of attention for book
Cover of 'Multiple Classifier Systems'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Semi-supervised Multiple Classifier Systems: Background and Research Directions
  3. Altmetric Badge
    Chapter 2 Boosting GMM and Its Two Applications
  4. Altmetric Badge
    Chapter 3 Boosting Soft-Margin SVM with Feature Selection for Pedestrian Detection
  5. Altmetric Badge
    Chapter 4 Observations on Boosting Feature Selection
  6. Altmetric Badge
    Chapter 5 Boosting Multiple Classifiers Constructed by Hybrid Discriminant Analysis
  7. Altmetric Badge
    Chapter 6 Decoding Rules for Error Correcting Output Code Ensembles
  8. Altmetric Badge
    Chapter 7 A Probability Model for Combining Ranks
  9. Altmetric Badge
    Chapter 8 EER of Fixed and Trainable Fusion Classifiers: A Theoretical Study with Application to Biometric Authentication Tasks
  10. Altmetric Badge
    Chapter 9 Mixture of Gaussian Processes for Combining Multiple Modalities
  11. Altmetric Badge
    Chapter 10 Dynamic Classifier Integration Method
  12. Altmetric Badge
    Chapter 11 Recursive ECOC for Microarray Data Classification
  13. Altmetric Badge
    Chapter 12 Using Dempster-Shafer Theory in MCF Systems to Reject Samples
  14. Altmetric Badge
    Chapter 13 Multiple Classifier Fusion Performance in Networked Stochastic Vector Quantisers
  15. Altmetric Badge
    Chapter 14 On Deriving the Second-Stage Training Set for Trainable Combiners
  16. Altmetric Badge
    Chapter 15 Using Independence Assumption to Improve Multimodal Biometric Fusion
  17. Altmetric Badge
    Chapter 16 Half-Against-Half Multi-class Support Vector Machines
  18. Altmetric Badge
    Chapter 17 Combining Feature Subsets in Feature Selection
  19. Altmetric Badge
    Chapter 18 ACE: Adaptive Classifiers-Ensemble System for Concept-Drifting Environments
  20. Altmetric Badge
    Chapter 19 Using Decision Tree Models and Diversity Measures in the Selection of Ensemble Classification Models
  21. Altmetric Badge
    Chapter 20 Ensembles of Classifiers from Spatially Disjoint Data
  22. Altmetric Badge
    Chapter 21 Optimising Two-Stage Recognition Systems
  23. Altmetric Badge
    Chapter 22 Design of Multiple Classifier Systems for Time Series Data
  24. Altmetric Badge
    Chapter 23 Ensemble Learning with Biased Classifiers: The Triskel Algorithm
  25. Altmetric Badge
    Chapter 24 Cluster-Based Cumulative Ensembles
  26. Altmetric Badge
    Chapter 25 Ensemble of SVMs for Incremental Learning
  27. Altmetric Badge
    Chapter 26 Design of a New Classifier Simulator
  28. Altmetric Badge
    Chapter 27 Evaluation of Diversity Measures for Binary Classifier Ensembles
  29. Altmetric Badge
    Chapter 28 Which Is the Best Multiclass SVM Method? An Empirical Study
  30. Altmetric Badge
    Chapter 29 Over-Fitting in Ensembles of Neural Network Classifiers Within ECOC Frameworks
  31. Altmetric Badge
    Chapter 30 Between Two Extremes: Examining Decompositions of the Ensemble Objective Function
  32. Altmetric Badge
    Chapter 31 Data Partitioning Evaluation Measures for Classifier Ensembles
  33. Altmetric Badge
    Chapter 32 Dynamics of Variance Reduction in Bagging and Other Techniques Based on Randomisation
  34. Altmetric Badge
    Chapter 33 Ensemble Confidence Estimates Posterior Probability
  35. Altmetric Badge
    Chapter 34 Using Domain Knowledge in the Random Subspace Method: Application to the Classification of Biomedical Spectra
  36. Altmetric Badge
    Chapter 35 An Abnormal ECG Beat Detection Approach for Long-Term Monitoring of Heart Patients Based on Hybrid Kernel Machine Ensemble
  37. Altmetric Badge
    Chapter 36 Speaker Verification Using Adapted User-Dependent Multilevel Fusion
  38. Altmetric Badge
    Chapter 37 Multi-modal Person Recognition for Vehicular Applications
  39. Altmetric Badge
    Chapter 38 Using an Ensemble of Classifiers to Audit a Production Classifier
  40. Altmetric Badge
    Chapter 39 Analysis and Modelling of Diversity Contribution to Ensemble-Based Texture Recognition Performance
  41. Altmetric Badge
    Chapter 40 Combining Audio-Based and Video-Based Shot Classification Systems for News Videos Segmentation
  42. Altmetric Badge
    Chapter 41 Designing Multiple Classifier Systems for Face Recognition
  43. Altmetric Badge
    Chapter 42 Exploiting Class Hierarchies for Knowledge Transfer in Hyperspectral Data
Attention for Chapter 28: Which Is the Best Multiclass SVM Method? An Empirical Study
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Mentioned by

wikipedia
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Readers on

mendeley
509 Mendeley
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1 CiteULike
Summary Wikipedia
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Chapter title
Which Is the Best Multiclass SVM Method? An Empirical Study
Chapter number 28
Book title
Multiple Classifier Systems
Published in
Lecture notes in computer science, June 2005
DOI 10.1007/11494683_28
Book ISBNs
978-3-54-026306-7, 978-3-54-031578-0
Authors

Kai-Bo Duan, S. Sathiya Keerthi, Duan, Kai-Bo, Keerthi, S. Sathiya

View on publisher site
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 509 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 12 2%
Germany 7 1%
United Kingdom 6 1%
Netherlands 4 <1%
France 4 <1%
India 3 <1%
China 3 <1%
Indonesia 2 <1%
Italy 2 <1%
Other 18 4%
Unknown 448 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 153 30%
Student > Master 93 18%
Researcher 77 15%
Student > Bachelor 36 7%
Student > Doctoral Student 20 4%
Other 78 15%
Unknown 52 10%
Readers by discipline Count As %
Computer Science 232 46%
Engineering 117 23%
Mathematics 19 4%
Agricultural and Biological Sciences 14 3%
Business, Management and Accounting 7 1%
Other 54 11%
Unknown 66 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 November 2021.
All research outputs
#7,451,584
of 22,780,967 outputs
Outputs from Lecture notes in computer science
#2,485
of 8,124 outputs
Outputs of similar age
#20,269
of 57,269 outputs
Outputs of similar age from Lecture notes in computer science
#14
of 67 outputs
Altmetric has tracked 22,780,967 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,124 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 57,269 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.

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