A computer scientist $(1)$ trains a machine learning system to identify patients with certain genetic diseases using a large dataset of labeled case histories, and $(2)$ instructs the system to suggest diagnostic protocols for such diseases that are more effective than those used in the dataset. These tasks are examples of$,$ respectively:

a$.(1)$ semi$-$supervised learning and $(2)$ expert systems

b$.(1)$ unsupervised and $(2)$ supervised learning

c$.(1)$ expert systems and $(2)$ genetic algorithms

d$.(1)$ supervised and $(2)$ semi$-$supervised learning

e$.(1)$ genetic algorithms and $(2)$ unsupervised learning