A Deep-Learning Prediction Model for Imbalanced Time Series Data Forecasting by Chenyu Hou, Jiawei Wu, Bin Cao, Jing Fan

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Surprise Bug Report Prediction Utilizing Optimized Integration with Imbalanced Learning Strategy by Hui Li, Yang Qu, Shikai Guo, Guofeng Gao, Rong Chen, Guo Chen

“…The main reason is that surprise bugs only occupy a small percentage of all the bugs, and it is difficult to identify these surprise bugs from the imbalanced distribution. In order to overcome the imbalanced category distribution of the bugs, a method based on machine learning to predict surprise bugs is presented in this paper. …”
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Imbalanced Data Sets Classification Based on SVM for Sand-Dust Storm Warning by Yonghua Xie, Yurong Liu, Qingqiu Fu

“…In view of the SVM classification for the imbalanced sand-dust storm data sets, this paper proposes a hybrid self-adaptive sampling method named SRU-AIBSMOTE algorithm. …”
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Corrigendum to “Imbalanced Regional Development of Acute Ischemic Stroke Care in Emergency Departments in China” by Jianguo Li, Jingming Liu, Yuefeng Ma, Peng Peng, Xiaojun He, Wei Guo

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IMBoost: A New Weighting Factor for Boosting to Improve the Classification Performance of Imbalanced Data by SeyedEhsan Roshan, Jafar Tanha, Farzad Hallaji, Mohammad-reza Ghanbari

“…Imbalanced datasets pose significant challenges in the field of machine learning, as they consist of samples where one class (majority) dominates over the other class (minority). …”
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Mass Cytometry Reveals the Imbalanced Immune State in the Peripheral Blood of Patients with Essential Hypertension by Rui Yang, Yuhong He, Honggang Zhang, Qiuju Zhang, Bingwei Li, Changming Xiong, Yubao Zou, Bingyang Liu

“…In conclusion, the altered number and antigen expression of immune cells reflect the imbalanced immune state of the peripheral blood in patients with EH.…”
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A Multi-Index Generative Adversarial Network for Tool Wear Detection with Imbalanced Data by Guokai Zhang, Haoping Xiao, Jingwen Jiang, Qinyuan Liu, Yimo Liu, Liying Wang

“…The scarcity of abnormal data leads to imbalanced data in the field of monitoring tool wear conditions. …”
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Imbalanced Fault Classification of Bearing via Wasserstein Generative Adversarial Networks with Gradient Penalty by Baokun Han, Sixiang Jia, Guifang Liu, Jinrui Wang

“…Recently, generative adversarial networks (GANs) are widely applied to increase the amounts of imbalanced input samples in fault diagnosis. However, the existing GAN-based methods have convergence difficulties and training instability, which affect the fault diagnosis efficiency. …”
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HSDP: A Hybrid Sampling Method for Imbalanced Big Data Based on Data Partition by Liping Chen, Jiabao Jiang, Yong Zhang

“…The classical classifiers are ineffective in dealing with the problem of imbalanced big dataset classification. Resampling the datasets and balancing samples distribution before training the classifier is one of the most popular approaches to resolve this problem. …”
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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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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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