Let's say we're going to train a classifier with the full data set. There's also a reject logic for ambiguous regions in the data. So, at the end, the final system outputs reject or 0 or 1. That is, reject data points in regions with high ambiguity, otherwise use the original model predictions.
- If you were to see a scatterplot with a boxplot accompanying it, how would you interpret the data in this plot?
- How would you reject ambiguous data points?