Consider decision tree algorithms, which splitting criterion should be used to balance the ability to create balanced branches in sizes and the ability to create pure children nodes?

$$a$)$ Minimize Gini impurity

$$b$)$ Minimize training error rate

$$c$)$ Maximize information gain

$$d$)$Maximize goodness of split