Which of the following is a weakness of Neural Networks?
a. "locally optimal solutions" rather than "globally optimal solutions"
b. Can only be used to model a narrow group of variables and non-linear functions
c. Results have low interpretability
d. None of the above



Answer :

Answer: a. "locally optimal solutions" rather than "globally optimal solutions"

Explanation:

Neural networks can sometimes get stuck in locally optimal solutions, where the network finds a solution that is optimal within a small region of the solution space but not necessarily the best possible solution globally. This can be a weakness because the network may not find the globally optimal solution for more complex problems.

Option b is incorrect because neural networks can model a wide range of variables and non-linear functions. This makes them quite versatile.

Option c is incorrect because while neural networks can have complex structures that make interpretation challenging, techniques like feature importance and visualization can help improve interpretability.