What is the role of the hyperparameter in SVM$\text{'}$s soft$-$margin formulation?

To specify the dimensionality of the feature space

To balance the trade$-$off between maximizing the margin and minimizing classification error

To control the degree of the polynomial kernel

To determine the number of support vectors