BACKGROUND Communities and nations seeking to foster social responsibility in their youth are interested in understanding factors that predict and promote youth involvement in public activities. Orphans and separated children (OSC) are a vulnerable population whose numbers are increasing, particularly in resource-poor settings. Understanding whether and how OSC are engaged in civic activities i...

We present three new voting schemes for multi-classifier biometric authentication using a reliability model to influence the importance of each base classifier’s vote. The reliability model is a metaclassifier computing the probability of a correct decision for the base classifiers. It uses two features which do not depend directly on the underlying physical signal properties, verification scor...

We introduce Learn++, an algorithm for incremental training of neural network (NN) pattern classifiers. The proposed algorithm enables supervised NN paradigms, such as the multilayer perceptron (MLP), to accommodate new data, including examples that correspond to previously unseen classes. Furthermore, the algorithm does not require access to previously used data during subsequent incremental l...

in this paper, a genetic algorithm is presented for an identical parallel-machine scheduling problem with family setup time that minimizes the total weighted flow time ( ). no set-up is necessary between jobs belonging to the same family. a set-up must be scheduled when switching from the processing of family i jobs to those of another family j, i  j, the duration of this set-up being the sequ...

For classifying time series, a nearest-neighbor approach is widely used in practice with performance often competitive with or better than more elaborate methods such as neural networks, decision trees, and support vector machines. We develop theoretical justification for the effectiveness of nearest-neighbor-like classification of time series. Our guiding hypothesis is that in many application...

The article shortly discusses the aim of classification task and its application to different domains of life. The idea of ensemble of classifiers is presented and some aspects of grouping methods are discussed. The paper points to the need of ensemble classifier pruning and presents a new approach for ensemble reduction. The proposed method is dedicated to committees of decision trees and base...

Automatic handwritten text recognition by computer has a number of interesting applications. However, due to a great variety of individual writing styles, the problem is very difficult and far from being solved. Recently, a number of classifier creation methods, known as ensemble methods, have been proposed in the field of machine learning. They have shown improved recognition performance over ...