The recent advancement in data science coupled with the revolution in digital and satellite
technology has improved the potential for artificial intelligence (AI) applications in the …

In many practical applications of supervised learning the task involves the prediction of
multiple target variables from a common set of input variables. When the prediction targets …

Groundwater quality monitoring in the vicinity of drilling sites is crucial for the protection of
water resources. Selected physicochemical parameters of waters were marked in the study …

Multi-target regression (MTR) comprises the prediction of multiple continuous target
variables from a common set of input variables. There are two major challenges when …

Accurate water quality time series prediction can provide support to early warning of water
pollution as well as decision-making for water resource management. Due to the uncertainty …

Multi-target models are machine learning models that simultaneously predict several target
attributes. Due to a high number of real-world applications, the field of multi-target prediction …

Ensemble methods based on-NN models minimise the effect of outliers in a training dataset
by searching groups of the closest data points to estimate the response of an unseen …

Multi-target regression (MTR) is an exciting area of machine learning where the challenge is
to predict the values of more than one target variables which can take on continuous values …

An appropriate management of the available resources within oceans and coastal regions is
vital to guarantee their sustainable development and preservation, where water quality is a …

This paper studies the greedy ensemble selection family of algorithms for ensembles of
regression models. These algorithms search for the globally best subset of regressors by …