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 …

The product quality indicators of the penicillin fermentation process have multiple semantics
and are interrelated. There is a complex nonlinear mapping relationship between input …

Choosing the most suitable algorithm to perform a machine learning task for a new problem
is a recurrent and complex task. In multi-target regression tasks, when problem …

Energy dispersive X-ray fluorescence (EDXRF) is one of the most quick, environmentally
friendly and least expensive spectroscopic analytical methodologies for assessing soil …

A fully automated and accurate assay of rare cell phenotypes in densely-packed
fluorescently-labeled liquid biopsy images remains elusive. Methods: Employing a hybrid …

An essential characteristic of data streams is the possibility of occurrence of concept drift, ie,
change in the distribution of the data in the stream over time. The capability to detect and …

Multi-target regression (MTR) has been widely studied in data analytics and its main
challenge is to jointly model the input-output relationships and the intrinsic inter-target …

Several multi-target regression methods were developed in the last years aiming at
improving predictive performance by exploring inter-target correlation within the problem …

A variable annuity (VA) is an insurance product that couples equity market investment with
some form of guaranteed return over a long time horizon. An initial investment is paid as a …

Although the impact of machine learning methods in the educational sciences has been
limited, recent opportunities have emerged that can benefit from these flexible methods …