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Ensembles of classifiers

Recently in the area of machine learning the concept of combining classifiers is proposed as a new direction for the improvement of the performance… 
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4 relations
Boosting (machine learning)Committee machine

Broader (2)

Ensemble learningMachine learning

Papers overview

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2015
2015
Contributions to Ensemble Classifiers with Image Analysis Applications
Esta tesis tiene dos aspectos fundamentales, por un lado, la propuesta denuevas arquitecturas de clasificadores y, por otro, su… 
2014
2014
Collective Classification of Posts to Internet Forums
We investigate automatic classification of posts to Internet forums. We use collective classification methods, which… 
2013
2013
Meta-ensembles of Classifiers for Alzheimer's Disease Detection Using Independent ROI Features
Due to its growing social impact, prodromal detection of Alzheimer’s disease is of paramount importance. Biomarkers based on… 
2012
2012
Evolution of heterogeneous ensembles through dynamic particle swarm optimization for video-based face recognition
2007
2007
Ambiguity-guided dynamic selection of ensemble of classifiers
Dynamic classifier selection has traditionally focused on selecting the most accurate classifier to predict the class of a… 
2007
2007
An empirical study on diversity measures and margin theory for ensembles of classifiers
The main goal of this paper is to investigate the relationship between two theories widely applied to explain the success of… 
2006
2006
Evolving ensemble of classifiers in random subspace
Various methods for ensemble selection and classifier combination have been designed to optimize the results of ensembles of… 
2004
2004
Ensembles of Classifiers Derived from Multiple Prototypes and Their Application to Handwriting Recognition
There are many examples of classification problems in the literature where multiple classifier systems increase the performance… 
2004
2004
Optimal resampling and classifier prototype selection in classifier ensembles using genetic algorithms
Ensembles of classifiers that are trained on different parts of the input space provide good results in general. As a popular… 
2000
2000
Combining Heterogeneous Sets of Classifiers : Theoretical and Experimental Comparison of Methods
In recent years, the combination of classifiers has been proposed as a method to improve the accuracy achieved in isolation by a… 
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