A data scientist is building a predictive model for a credit scoring system and decides to use cross$-$validation to evaluate its performance. What is the primary advantage of using cross$-$validation in this context?

Group of answer choices

It reduces the computational time required to train the model.

It provides a more reliable estimate of model performance by using multiple training and validation splits.

It eliminates the need for feature selection.

It ensures that the model will perform well on unseen data without any further validation.