Multiple Classifier Systems - Lecture Notes in Computer Science
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Published By Springer Berlin Heidelberg

9783642121265, 9783642121272

Latest Documents Most Cited Documents Contributed Authors Related Sources Related Keywords

Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_24 ◽

2010 ◽

pp. 235-244 ◽

Cited By ~ 14

Author(s):

Nabiha Azizi ◽

Nadir Farah ◽

Mokhtar Sellami ◽

Abdel Ennaji

Keyword(s):

Selection For ◽

Handwritten Recognition

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Dynamic Selection of Ensembles of Classifiers Using Contextual Information

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_15 ◽

2010 ◽

pp. 145-154 ◽

Cited By ~ 5

Author(s):

Paulo R. Cavalin ◽

Robert Sabourin ◽

Ching Y. Suen

Keyword(s):

Contextual Information ◽

Dynamic Selection ◽

Ensembles Of Classifiers ◽

Selection Of

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Choosing Parameters for Random Subspace Ensembles for fMRI Classification

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_6 ◽

2010 ◽

pp. 54-63 ◽

Cited By ~ 10

Author(s):

Ludmila I. Kuncheva ◽

Catrin O. Plumpton

Keyword(s):

Random Subspace

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Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_4 ◽

2010 ◽

pp. 33-42 ◽

Cited By ~ 14

Author(s):

Gregory Ditzler ◽

Michael D. Muhlbaier ◽

Robi Polikar

Keyword(s):

Incremental Learning

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An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_30 ◽

2010 ◽

pp. 294-303 ◽

Cited By ~ 4

Author(s):

Matteo Re ◽

Giorgio Valentini

Keyword(s):

Protein Function ◽

Protein Function Prediction ◽

Function Prediction ◽

Hierarchical Bayes ◽

Experimental Comparison ◽

True Path

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Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_2 ◽

2010 ◽

pp. 11-21 ◽

Cited By ~ 9

Author(s):

Muhammad Atif Tahir ◽

Josef Kittler ◽

Krystian Mikolajczyk ◽

Fei Yan

Keyword(s):

Classification Performance ◽

Multilabel Classification

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A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_17 ◽

2010 ◽

pp. 165-174 ◽

Cited By ~ 9

Author(s):

Alexander Tatarchuk ◽

Eugene Urlov ◽

Vadim Mottl ◽

David Windridge

Keyword(s):

Pattern Recognition ◽

Kernel Machine ◽

Diverse Pattern

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Some Thoughts at the Interface of Ensemble Methods and Feature Selection

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_32 ◽

2010 ◽

pp. 314-314 ◽

Cited By ~ 4

Author(s):

Gavin Brown

Keyword(s):

Feature Selection ◽

Ensemble Methods

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New Feature Splitting Criteria for Co-training Using Genetic Algorithm Optimization

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_3 ◽

2010 ◽

pp. 22-32 ◽

Cited By ~ 6

Author(s):

Ahmed Salaheldin ◽

Neamat El Gayar

Keyword(s):

Genetic Algorithm ◽

Algorithm Optimization ◽

Genetic Algorithm Optimization ◽

New Feature

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SOCIAL: Self-Organizing ClassIfier ensemble for Adversarial Learning

Multiple Classifier Systems - Lecture Notes in Computer Science ◽

10.1007/978-3-642-12127-2_9 ◽

2010 ◽

pp. 84-93 ◽

Cited By ~ 3

Author(s):

Francesco Gargiulo ◽

Carlo Sansone

Keyword(s):

Classifier Ensemble ◽

Social Self ◽

Adversarial Learning ◽

Self Organizing

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Multiple Classifier Systems - Lecture Notes in Computer ScienceLatest Publications

TOTAL DOCUMENTS

H-INDEX

Published By Springer Berlin Heidelberg

Using Diversity in Classifier Set Selection for Arabic Handwritten Recognition

Dynamic Selection of Ensembles of Classifiers Using Contextual Information

Choosing Parameters for Random Subspace Ensembles for fMRI Classification

Incremental Learning of New Classes in Unbalanced Datasets: Learn + + .UDNC

An Experimental Comparison of Hierarchical Bayes and True Path Rule Ensembles for Protein Function Prediction

Improving Multilabel Classification Performance by Using Ensemble of Multi-label Classifiers

A Support Kernel Machine for Supervised Selective Combining of Diverse Pattern-Recognition Modalities

Some Thoughts at the Interface of Ensemble Methods and Feature Selection

New Feature Splitting Criteria for Co-training Using Genetic Algorithm Optimization

SOCIAL: Self-Organizing ClassIfier ensemble for Adversarial Learning

Multiple Classifier Systems - Lecture Notes in Computer Science
Latest Publications