Given a dataset with known class labels $($ground truth$)(f(0))$ of the objects. The dataset contains binary labels of

positive $(+)$ instances and negative $((-)$ instances. In order to evaluate the quality of a classifier $h,$ each object is

additionally classified using $h.$ The results are given in the table below. How many false negatives does the

classifier make?

a$.4$

b$.2$

c$.$ None

d$.5$

e$.3$