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Luca Scrucca
Imbalanced data present a pervasive challenge in many real-world applications of statistical and machine learning, where the instances of one class significantly outnumber those of the other. This paper examines the impact of class imbalance on the perfo...
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Maria Carmela Groccia, Rosita Guido, Domenico Conforti, Corrado Pelaia, Giuseppe Armentaro, Alfredo Francesco Toscani, Sofia Miceli, Elena Succurro, Marta Letizia Hribal and Angela Sciacqua
Chronic heart failure (CHF) is a clinical syndrome characterised by symptoms and signs due to structural and/or functional abnormalities of the heart. CHF confers risk for cardiovascular deterioration events which cause recurrent hospitalisations and hig...
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Fen Liu and Quan Qian
Classification is among the core tasks in machine learning. Existing classification algorithms are typically based on the assumption of at least roughly balanced data classes. When performing tasks involving imbalanced data, such classifiers ignore the m...
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Maya Hilda Lestari Louk and Bayu Adhi Tama
Classifier ensembles have been utilized in the industrial cybersecurity sector for many years. However, their efficacy and reliability for intrusion detection systems remain questionable in current research, owing to the particularly imbalanced data issu...
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Barbara Pes
Class imbalance and high dimensionality are two major issues in several real-life applications, e.g., in the fields of bioinformatics, text mining and image classification. However, while both issues have been extensively studied in the machine learning ...
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Mahdi Rezapour and Khaled Ksaibati
Road departure crashes tend to be hazardous, especially in rural areas like Wyoming. Traffic barriers could be installed to mitigate the severity of those crashes. However, the severity of traffic barriers crashes still persists. Besides various drivers ...
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Xingquan Zhu; Xindong Wu
Pág. 1435 - 1440
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