How can cross$-$validation help in managing overfitting? $($Multi$-$choice$)$

Options:

a$.$ It forces the model to generalize better across different subsets of the data.

b$.$ It ensures the model is trained on less data to make it more robust.

c$.$ It divides the dataset into multiple subsets to ensure the model is evaluated on different data portions.

d$.$ It provides a more reliable estimate of model performance on unseen data.

e$.$ It eliminates the need for separate training and validation datasets.