Editing Training Data for kNN Classifiers with Neural Network Ensemble

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Learning kernel logistic regression in the presence of class label noise (2014, background): “The seemingly straightforward approach is by means of data preprocessing where any suspect samples are removed or relabelled [7,1,29,37,31,18].”
Automatic Adaptation of Object Detectors to New Domains Using Self-Training (2019, unknown): “A subset of these estimated labels that are most likely to be correct are selected and used to re-train the baseline model, and the process continues in an incremental fashion [39, 33, 37, 24, 63].”
Label-Noise Robust Logistic Regression and Its Applications (2012, background): “The seemingly straightforward approach is by means of data preprocessing where any suspect samples are removed or relabelled [3, 2, 9].”