Predicting Nurse Turnover for Highly Imbalanced Data Using the Synthetic Minority Over-Sampling Technique and Machine Learning Algorithms. [PDF]
Healthcare (Basel), 2023 Xu Y, Park Y, Park JD, Sun B.
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A Gradient-Penalized Conditional TimeGAN Combined with Multi-Scale Importance-Aware Network for Fault Diagnosis Under Imbalanced Data. [PDF]
Sensors (Basel)Deng R +5 more
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Odor classification: Exploring feature performance and imbalanced data learning techniques. [PDF]
PLoS OneAmeta D +5 more
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An empirical evaluation of sampling methods for the classification of imbalanced data. [PDF]
PLoS One, 2022 Kim M, Hwang KB.
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An improved SMOTE algorithm for enhanced imbalanced data classification by expanding sample generation space. [PDF]
Sci RepLi Y, Yang Y, Song P, Duan L, Ren R.
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An Explainable Machine Learning Pipeline for Stroke Prediction on Imbalanced Data. [PDF]
Diagnostics (Basel), 2022 Kokkotis C +7 more
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Improving Gaussian Naive Bayes classification on imbalanced data through coordinate-based minority feature mining. [PDF]
PeerJ Comput SciWang W, Yan L, Liu F, Li Y.
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Imbalanced data preprocessing techniques for machine learning: a systematic mapping study. [PDF]
Knowl Inf Syst, 2023 Werner de Vargas V +4 more
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Intelligent approach to detecting online fraudulent trading with solution for imbalanced data in fintech forensics. [PDF]
Sci RepDarwish SM, Salama AI, Elzoghabi AA.
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Association rule mining of time-based patterns in diabetes-related comorbidities on imbalanced data: a pre- and post-diagnosis study. [PDF]
BMC Med Inform Decis MakBata R +4 more
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