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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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Jose Luis Vieira Sobrinho, Flavio Henrique Teles Vieira and Alisson Assis Cardoso
The high dimensionality of real-life datasets is one of the biggest challenges in the machine learning field. Due to the increased need for computational resources, the higher the dimension of the input data is, the more difficult the learning task will ...
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Falah Amer Abdulazeez, Ismail Taha Ahmed and Baraa Tareq Hammad
A significant quantity of malware is created on purpose every day. Users of smartphones and computer networks now mostly worry about malware. These days, malware detection is a major concern in the cybersecurity area. Several factors can impact malware d...
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Lianlian He, Hao Li and Rui Zhang
Recent advances in knowledge graphs show great promise to link various data together to provide a semantic network. Place is an important part in the big picture of the knowledge graph since it serves as a powerful glue to link any data to its georeferen...
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Xiaonan Si, Lei Wang, Wenchang Xu, Biao Wang and Wenbo Cheng
Gout is one of the most painful diseases in the world. Accurate classification of gout is crucial for diagnosis and treatment which can potentially save lives. However, the current methods for classifying gout periods have demonstrated poor performance a...
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Niwan Wattanakitrungroj, Pimchanok Wijitkajee, Saichon Jaiyen, Sunisa Sathapornvajana and Sasiporn Tongman
For the financial health of lenders and institutions, one important risk assessment called credit risk is about correctly deciding whether or not a borrower will fail to repay a loan. It not only helps in the approval or denial of loan applications but a...
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Xuefeng Zhang, Youngsung Kim, Young-Chul Chung, Sangcheol Yoon, Sang-Yong Rhee and Yong Soo Kim
Large-scale datasets, which have sufficient and identical quantities of data in each class, are the main factor in the success of deep-learning-based classification models for vision tasks. A shortage of sufficient data and interclass imbalanced data dis...
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Amani Alqarni and Hamoud Aljamaan
Software defect prediction is an active research area. Researchers have proposed many approaches to overcome the imbalanced defect problem and build highly effective machine learning models that are not biased towards the majority class. Generative adver...
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Samuel Ndichu, Tao Ban, Takeshi Takahashi and Daisuke Inoue
Intrusion analysis is essential for cybersecurity, but oftentimes, the overwhelming number of false alerts issued by security appliances can prove to be a considerable hurdle. Machine learning algorithms can automate a task known as security alert data a...
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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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