It is known that tree-based learning is unstable.

What does this mean?

a. Trees are poor predictive models.

b. The predictive performance of the tree varies dramatically based on the training data used.

c. When the data used to train a tree is changed (even slightly), the variables (and their split values) composing the tree structure may vary dramatically.

d. Trees are difficult to interpret and explain.