In many applications of information systems learning algorithms have to act in dynamic
environments where data are collected in the form of transient data streams. Compared to …

This paper presents a comprehensive review of evolutionary algorithms that learn an
ensemble of predictive models for supervised machine learning (classification and …

One of the most challenging issues when facing a classification problem is to deal with
imbalanced datasets. Recently, ensemble classification techniques have proven to be very …

Accurate rainfall measurements are essential for many applications including watershed
management and hydrological modeling. This is particularly true in sub-Saharan Africa …

Purpose Real estate appraisals are becoming an increasingly important means of backing
up financial operations based on the values of these kinds of assets. However, in very large …

Classification is the machine learning task of categorizing instances into classes. There are
several algorithms in the literature that perform classification, with varying degrees of …