Machine Learning Classifiers and Data Synthesis Techniques to Tackle with Highly Imbalanced COVID-19 Data by Avaz Naghipour, Mohammad Reza Abbaszadeh Bavil Soflaei, mostafa ghader-zefrehei

“…In this study, we evaluate three machine learning models—Random Forest (RF), Logistic Regression (LR) and Decision Tree (DT)—for detecting COVID-19 trained on preprocessed imbalanced datasets with 5086 negative and 558 positive cases. …”
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Fault and Severity Diagnosis Using Deep Learning for Self-Organizing Networks With Imbalanced and Small Datasets by Hsin-Chang Tsai, Ming-Chun Lee, Chao-Hao Hsu

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A Novel Stacked Model for Classification of Vocal Cord Paralysis Over Imbalanced Vocal Data by K. Jayashree Hegde, K. Manjula Shenoy, K. Devaraja

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Data Augmentation and Machine Learning algorithms for multi-class imbalanced morphometrics data of stingless bees by Daisy Salifu, Lorna Chepkemoi, Eric Ali Ibrahim, Kiatoko Nkoba, Henri E.Z. Tonnang

Subjects: “…Imbalanced data…”
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Influence maximization under imbalanced heterogeneous networks via lightweight reinforcement learning with prior knowledge by Kehong You, Sanyang Liu, Yiguang Bai

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Predicting Postoperative Re-Tear of Arthroscopic Rotator Cuff Repair Using Artificial Intelligence on Imbalanced Data by Zhibin Zhang, Zhewei Zhang, Zhaoxiang Peng, Yihong Dong

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Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data by Mihkel Kotli, Geven Piir, Uko Maran

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Improving Sentiment Analysis Performance on Imbalanced Moroccan Dialect Datasets Using Resample and Feature Extraction Techniques by Zineb Nassr, Faouzia Benabbou, Nawal Sael, Touria Hamim

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Algoritma K-Nearest Neighbor pada Kasus Dataset Imbalanced untuk Klasifikasi Kinerja Karyawan Perusahaan by Fitri Nuraeni, Dede Kurniadi, Moch Haiqal Diazki

Subjects: “…Imbalanced Dataset…”
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3D-AOCL: Analytic online continual learning for imbalanced 3D point cloud classification by Ziqian Zeng, Jianwei Wang, Lin Wu, Weikai Lu, Huiping Zhuang

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Low-resource MobileBERT for emotion recognition in imbalanced text datasets mitigating challenges with limited resources. by Muhammad Hussain, Caikou Chen, Sami S Albouq, Khlood Shinan, Fatmah Alanazi, Muhammad Waseem Iqbal, M Usman Ashraf

“…Our proposed loss function handles the problem of imbalanced emotion classification through Focal Weighted Loss and adversarial training and does not require large batch sizes or more computational resources. …”
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Leveraging generative adversarial networks for data augmentation to improve fault detection in wind turbines with imbalanced data by Subhajit Chatterjee, Yung-Cheol Byun

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Retracted: The Use of Hellinger Distance Undersampling Model to Improve the Classification of Disease Class in Imbalanced Medical Datasets by Applied Bionics and Biomechanics

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Features of Administrative and Legal Regulation of Protecting Forestry Fund Land in Ukraine by R. V. Igonin, M. V. Viktorchuk

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Class Weighting Approach For Handling Imbalanced Data On Forest Fire Classification Using EfficientNet-B1 by Arvinanto Bahtiar, Muhammad Ihsan Prawira Hutomo, Agung Widiyanto, Siti Khomsah

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Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework by Ruize Gao, Shaoze Cui, Yu Wang, Wei Xu

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Advanced R-GAN: Generating anomaly data for improved detection in imbalanced datasets using regularized generative adversarial networks by Junhak Lee, Dayeon Jung, Jihoon Moon, Seungmin Rho

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Optimizing Classification Decision Trees by Using Weighted Naïve Bayes Predictors to Reduce the Imbalanced Class Problem in Wireless Sensor Network by Hang Yang, Simon Fong, Raymond Wong, Guangmin Sun

“…Standard classification algorithms are often inaccurate when used in a wireless sensor network (WSN), where the observed data occur in imbalanced classes. The imbalanced data classification problem occurs when the number of samples in one class, usually the class of interest, is much lower than the number in the other classes. …”
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Cost-Sensitive Support Vector Machine Using Randomized Dual Coordinate Descent Method for Big Class-Imbalanced Data Classification by Mingzhu Tang, Chunhua Yang, Kang Zhang, Qiyue Xie

“…Cost-sensitive support vector machine is one of the most popular tools to deal with class-imbalanced problem such as fault diagnosis. However, such data appear with a huge number of examples as well as features. …”
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NF-κB-94ins/del ATTG Genotype Contributes to the Susceptibility and Imbalanced Th17 Cells in Patients with Immune Thrombocytopenia by Jie Yu, Mingqiang Hua, Xueyun Zhao, Rui Wang, Chaoqing Zhong, Chen Zhang, Ruiqing Wang, Guosheng Li, Na He, Ming Hou, Daoxin Ma

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