A model with a high bias is likely to underfit the training set. Let's consider the scenario shown in the following graph:
Underfitted classifier: The curve cannot separate correctly the two classes
Even if the problem is very hard, we could try to adopt a linear model and, at the end of the training process, the slope and the intercept of the separating line are about -1 and 0 (as shown in the plot); however, if we measure the accuracy, we discover that it's close to 0! Independently from the number of iterations, this model will never be able to learn the association between X and Y. This condition is called underfitting, and ...
