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… (More)
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Papers overview

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2017
2017
We present a novel approach for the construction of ensemble classifiers based on dimensionality reduction. Dimensionality… (More)
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Highly Cited
2015
Highly Cited
2015
Recently, two ideas have been explored that lead to more accurate algorithms for time-series classification (TSC). First, it has… (More)
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2015
2015
In Machine Learning, a data set is imbalanced when the class proportions are highly skewed. Imbalanced data sets arise routinely… (More)
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2014
2014
It is studied how to aggregate the probabilistic predictions generated by different SPODE (Super-Parent-One-Dependence Estimators… (More)
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2008
2008
An ensemble of classifiers is a set of classifiers whose predictions are combined in some way to classify new instances. Early… (More)
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2007
2007
We present a method for building ensembles of models in order to build proper classifiers. The main advantage of our method is an… (More)
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Highly Cited
2006
Highly Cited
2006
We propose a method for generating classifier ensembles based on feature extraction. To create the training data for a base… (More)
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Highly Cited
2004
Highly Cited
2004
We study the issue of error diversity in ensembles of neural networks. In ensembles of regression estimators, the measurement of… (More)
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Highly Cited
2003
Highly Cited
2003
Combination (ensembles) of classifiers is now a well established research line. It has been observed that the predictive accuracy… (More)
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Highly Cited
2001
Highly Cited
2001
It is well known that ensembles of predictors produce better accuracy than a single predictor provided there is diversity in the… (More)
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