Fig. 7
From: Addressing label noise for electronic health records: insights from computer vision for tabular data
Predicted confidence of correctly labeled and incorrectly labeled training examples during different stages of training. a shows the predicted confidences when using Baseline NN trained using only cross entropy (CE) loss and b that of the same model when trained using CE+NCR loss terms