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Evaluating the three-level approach of the U-smile method for imbalanced binary classification

Fig 5

U-smile plots of the subclass-specific BA-RB-I coefficients across imbalance ranging from 1% to 99% of the event class, for four new models derived from the test dataset.

Two informative variables (ST depression and Str Rnd normal) and two non-informative variables (glucose and Rnd normal) were added to the reference model. The plotted coefficient values represent means from 1000 iterations. The I coefficient is the weighting factor for point size. BA coefficients: average absolute changes in prediction between new and reference models; RB coefficients: relative changes in prediction between new and reference models (relative to the reference prediction error); I coefficients: proportions of individuals with prediction changes in each class.

Fig 5

doi: https://doi.org/10.1371/journal.pone.0321661.g005