While diversity of ensembles has been studied in the context of static data, it has not still
received such research interest for evolving data streams. This paper aims at analyzing the …

基于天绘一号(TH-1, 或称MS-1) 卫星多光谱数据, 采用随机森林分类方法(random forests
classification, RFC) 对位于中亚干旱区的我国新疆维吾尔自治区阿勒泰地区北屯市及周边区域 …

Landslide scar location is fundamental for the risk management process, eg, it allows
mitigation of these areas, decreasing the associated hazards for the population. Remote …

In the classification task, the ensemble selection methods reduce the available pool of the
base classifiers. The dynamic ensemble selection methods allow to find the subset of base …

Type and structure of artificial neural network (ANN) have significant impact on its
performance. Furthermore, networks of the same type and structure often perform differently …

In the classification task, the ensemble of classifiers have attracted more and more attention
in pattern recognition communities. Generally, ensemble methods have the potential to …

Generally, information system handles huge volume of dataset. Classifiers provide poor
performance when such dataset are feed into it for categorization due to their high …

Glaucoma is a group of eye diseases caused due to excessively high intraocular pressure
within the eye. Ensemble classifier construction has attracted increasing interest in the field …

The dynamic selection of classifiers plays an important role in the creation of an ensemble of
classifiers. The paper presents the dynamic selection of a posteriori probability function …

The ensemble selection is one of the important problems in building multiple classifier
systems (MCSs). This paper presents dynamic ensemble selection based on the analysis of …