How does gradient boosting work?
a. It forms a strong learner by discarding mistakes from prior test iterations.
b. It generates a range of input conditions for a machine learning model to test with.
c. It combines weak learners together to form a strong learner by improving on mistakes from prior test iterations.
d. It generates boundary conditions for a machine learning model to test with.