Our hypothesis is that building ensembles of small sets of strong classifiers constructed with
different learning algorithms is, on average, the best approach to classification for real-world …

A method of stance detection in text is proposed. This method is based on the machine
learning of ensembles of classifiers. It is known that ensembles have advantages over …

This paper proposes a new ensemble feature selector, called the majority voting feature
selector (MVFS), for developing new maximal oxygen uptake (VO2max) prediction models …

Diabetes disease occurs when the level of glucose in the blood becomes higher than
normal because the body is unable to produce the insulin which is needed to regulate …

В статье предложен метод решения задачи определения точки зрения автора
текстового документа, основанный на машинном обучении ансамблей …

Ensemble classifiers are methods which aggregate the predictions of a number of diverse
base classifiers in order to produce a more accurate predictor, with the idea being that many …

An ensemble of classifiers can improve the performance of a pattern recognition system. The
task of constructing multiple classifier systems can be generally divided into three steps …

Neural networks are an important tool in the field of data science as well as in the study of
the very structures they were inspired from ie the human nervous system. In this dissertation …

Estimations and predictions of surface water runoff can provide very useful insights,
regarding flood risks in urban areas. To automatically predict the flow behaviour of the …