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Panagiotis Pintelas and Ioannis E. Livieris
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Panagiotis Pintelas and Ioannis E. Livieris
During the last decades, in the area of machine learning and data mining, the development of ensemble methods has gained a significant attention from the scientific community. Machine learning ensemble methods combine multiple learning algorithms to obta...
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Ioannis E. Livieris, Emmanuel Pintelas, Stavros Stavroyiannis and Panagiotis Pintelas
Nowadays, cryptocurrency has infiltrated almost all financial transactions; thus, it is generally recognized as an alternative method for paying and exchanging currency. Cryptocurrency trade constitutes a constantly increasing financial market and a prom...
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Ioannis E. Livieris, Spiros D. Dafnis, George K. Papadopoulos and Dionissios P. Kalivas
Cotton constitutes a significant commercial crop and a widely traded commodity around the world. The accurate prediction of its yield quantity could lead to high economic benefits for farmers as well as for the rural national economy. In this research, w...
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Emmanuel Pintelas, Ioannis E. Livieris and Panagiotis Pintelas
Machine learning has emerged as a key factor in many technological and scientific advances and applications. Much research has been devoted to developing high performance machine learning models, which are able to make very accurate predictions and decis...
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Ioannis E. Livieris
During the last few decades, machine learning has constituted a significant tool in extracting useful knowledge from economic data for assisting decision-making. In this work, we evaluate the performance of weight-constrained recurrent neural networks in...
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Ioannis E. Livieris, Andreas Kanavos, Vassilis Tampakas and Panagiotis Pintelas
During the last decades, intensive efforts have been devoted to the extraction of useful knowledge from large volumes of medical data employing advanced machine learning and data mining techniques. Advances in digital chest radiography have enabled resea...
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Ioannis E. Livieris
In this work, a new approach for training artificial neural networks is presented which utilises techniques for solving the constraint optimisation problem. More specifically, this study converts the training of a neural network into a constraint optimis...
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Ioannis E. Livieris, Niki Kiriakidou, Andreas Kanavos, Vassilis Tampakas and Panagiotis Pintelas
Credit scoring is generally recognized as one of the most significant operational research techniques used in banking and finance, aiming to identify whether a credit consumer belongs to either a legitimate or a suspicious customer group. With the vigoro...
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Ioannis E. Livieris, Andreas Kanavos, Vassilis Tampakas and Panagiotis Pintelas
Semi-supervised learning algorithms have become a topic of significant research as an alternative to traditional classification methods which exhibit remarkable performance over labeled data but lack the ability to be applied on large amounts of unlabele...
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