Clustering and classification for dry bean feature imbalanced data. [PDF]
Sci RepLee CY, Wang W, Huang JQ.
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Addressing imbalanced data classification with Cluster-Based Reduced Noise SMOTE. [PDF]
PLoS OneHemmatian J, Hajizadeh R, Nazari F.
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Approaches for handling imbalanced data used in machine learning in the healthcare field: A case study on Chagas disease database prediction. [PDF]
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Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data. [PDF]
Diagnostics (Basel)Al-Ahmari S, Nadeem F.
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Entropy-based dynamic ensemble classication algorithm for imbalanced data stream with concept drift. [PDF]
PLoS OneGong J, Dong M.
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A Candy Defect Detection Method Based on StyleGAN2 and Improved YOLOv7 for Imbalanced Data. [PDF]
FoodsLi X, Xue S, Li Z, Fang X, Zhu T, Ni C.
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Optimal intrusion detection for imbalanced data using Bagging method with deep neural network optimized by flower pollination algorithm. [PDF]
PeerJ Comput SciSayegh HR +4 more
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Predictive Modeling of Pesticides Reproductive Toxicity in Earthworms Using Interpretable Machine-Learning Techniques on Imbalanced Data. [PDF]
ACS OmegaKotli M, Piir G, Maran U.
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A Cross-Machine Intelligent Fault Diagnosis Method with Small and Imbalanced Data Based on the ResFCN Deep Transfer Learning Model. [PDF]
Sensors (Basel)Zhao J, Yuan M, Cui Y, Cui J.
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Correction: An explainable ensemble approach for advanced brain tumor classification applying Dual-GAN mechanism and feature extraction techniques over highly imbalanced data. [PDF]
PLoS OnePLOS One Staff.
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