Several pruning strategies that can be used to reduce the size and increase the accuracy of
bagging ensembles are analyzed. These heuristics select subsets of complementary …

Ensemble selection deals with the reduction of an ensemble of predictive models in order to
improve its efficiency and predictive performance. A number of ensemble selection methods …

Fall prevention lacks easy, quantitative and wearable methods for the classification of fall-
risk (FR). Efforts must be thus devoted to the choice of an ad hoc classifier both to reduce the …

Different data classification algorithms have been developed and applied in various areas to
analyze and extract valuable information and patterns from large datasets with noise and …

In the context of Ensembles or Multi-Classifier Systems, the choice of the ensemble
members is a very complex task, in which, in some cases, it can lead to ensembles with no …

The test set accuracy for ensembles of classifiers selected based on single measures of
accuracy and diversity as well as combinations of such measures is investigated. It is found …

Non-parametric classification procedures based on a certainty measure and nearest
neighbour rule for motor unit potential classification (MUP) during electromyographic (EMG) …

Because of the high request to classifiers performance of people and the implementation
complexity of multiple classifiers ensemble approach, this paper proposes a new method of …

This article concerns methods of improving the accuracy of land cover maps using Very High-
resolution Satellites (VHRS). It discusses two methods for increasing the accuracy of …

Cancer classification using gene expression data has the great importance in bioinformatics
and is known to contain the keys for addressing the fundamental problems relating to cancer …