A unified, coherent treatment of current classifier ensemble methods, from fundamentals of
pattern recognition to ensemble feature selection, now in its second edition The art and …

In the paper we present some guidelines for the application of nonparametric statistical tests
and post-hoc procedures devised to perform multiple comparisons of machine learning …

Currently, methods of combined classification are the focus of intense research. A properly
designed group of combined classifiers exploiting knowledge gathered in a pool of …

The unequal area facility layout problem (UA‐FLP) has been addressed by many methods.
Most of them only take aspects that can be quantified into account. This contribution …

The crucial problem that has to be solved when designing an effective brain–computer
interface (BCI) is: how to reduce the huge space of features extracted from raw …

Predicting consumer sentiments revealed in online reviews is crucial to suppliers and
potential consumers. We combine online sequential extreme learning machines (OS-ELMs) …

摘要针对多分类器系统设计中最优子集选择效率低下, 集成方法缺乏灵活性等问题,
提出了分类器的动态选择与循环集成方法(Dynamic selection and circulating combination …

There has been much work in establishing joint replenishment model and designing
effective and robust algorithms. Little research has been done by direct grouping methods …

This paper presents a novel ensemble classifier system designed to process data streams
featuring occasional changes in their characteristics (concept drift). The ensemble is …

The problem of model selection to compose a heterogeneous bagging ensemble was
addressed in the paper. To solve the problem, three self-adapting genetic algorithms were …