Select all correct statement$($s$)$ about decision tree and random forest methods:

$($a$)$ Using less decision trees to form a random forest tends to decrease overfitting.

$($b$)$ Entropy, Gini Index and Misclassification Error are all valid options for feature selection in

the decision tree method.

$($c$)$ Random forest method is more interpretable than decision tree method.

$($d$)$ In decision trees, the depth of the tree can be adjusted to control model complexity and avoid

overfitting