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Maryam Badar and Marco Fisichella
Fairness-aware mining of data streams is a challenging concern in the contemporary domain of machine learning. Many stream learning algorithms are used to replace humans in critical decision-making processes, e.g., hiring staff, assessing credit risk, et...
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Firas Alghanim, Ibrahim Al-Hurani, Hazem Qattous, Abdullah Al-Refai, Osamah Batiha, Abedalrhman Alkhateeb and Salama Ikki
Identifying menopause-related breast cancer biomarkers is crucial for enhancing diagnosis, prognosis, and personalized treatment at that stage of the patient?s life. In this paper, we present a comprehensive framework for extracting multiomics biomarkers...
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Yong Liu, Jialin Zhou, Dong Zhang, Shaoyu Wei, Mingshun Yang and Xinqin Gao
To solve the problem of low diagnostic accuracy caused by the scarcity of fault samples and class imbalance in the fault diagnosis task of box-type substations, a fault diagnosis method based on self-attention improvement of conditional tabular generativ...
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Syed As-Sadeq Tahfim and Yan Chen
Severe and fatal crashes involving large trucks result in significant social and economic losses for human society. Unfortunately, the notably low proportion of severe and fatal injury crashes involving large trucks creates an imbalance in crash data. Mo...
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Samuel de Oliveira, Oguzhan Topsakal and Onur Toker
Automated Machine Learning (AutoML) is a subdomain of machine learning that seeks to expand the usability of traditional machine learning methods to non-expert users by automating various tasks which normally require manual configuration. Prior benchmark...
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Zhichao Chen, Guoqiang Wang, Tao Lv and Xu Zhang
Diseases of tomato leaves can seriously damage crop yield and financial rewards. The timely and accurate detection of tomato diseases is a major challenge in agriculture. Hence, the early and accurate diagnosis of tomato diseases is crucial. The emergenc...
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Jiaming Song, Xiaojuan Wang, Mingshu He and Lei Jin
In computer networks, Network Intrusion Detection System (NIDS) plays a very important role in identifying intrusion behaviors. NIDS can identify abnormal behaviors by analyzing network traffic. However, the performance of classifier is not very good in ...
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Hongpo Zhang, Bo Zhang, Lulu Huang, Zhaozhe Zhang and Haizhaoyang Huang
Internet of Things (IoT) devices and services provide convenience but face serious security threats. The network intrusion detection system is vital in ensuring the security of the IoT environment. In the IoT environment, we propose a novel two-stage int...
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Patience Chew Yee Cheah, Yue Yang and Boon Giin Lee
The class imbalance problem in finance fraud datasets often leads to biased prediction towards the nonfraud class, resulting in poor performance in the fraud class. This study explores the effects of utilizing the Synthetic Minority Oversampling TEchniqu...
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Choong Hee Cho, Yang Woo Yu and Hyeon Gyu Kim
Student dropout is a serious issue in that it not only affects the individual students who drop out but also has negative impacts on the former university, family, and society together. To resolve this, various attempts have been made to predict student ...
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