Underfitting is the phenomenon of a model not performing well, i.e., not making good predictions, because it wasn’t able to correctly or completely capture the signal in the training set. In other words, the model is generalizing too much, to the...

It’s the process of balancing a data set by discarding examples of the overrepresented class so that each has the same amount of examples. A balanced data set allows a model to learn equal amounts of characteristics from each one of the classes...