Let’s consider a classification problem (similar to one that we have seen so far in the book). While doing all our work we made a strong assumption without explicitly saying it: we assume that all the observations are correctly labelled! We cannot say that with certainty. To perform the labelling, we needed some manual intervention, and therefore there must be a certain number of images that are improperly classified since humans are not perfect. This is an important revelation.
Consider the following scenario: we are supposed to reach 90% accuracy in a classification ...
