There are two main goals of developing this classifier: (1) accurately predicting the labels of data points and ranking them based on prediction confidence, so that the most likely errors can be effectively identified; (2) requiring less time on training, so that the saved time can be spent on correcting more labeling errors.
we aim to build a classifier that is both accurate and time efficient.