A classification tree, which is a model used for decision$-$making in

machine learning, demonstrates the most effective performance when it

possesses the highest cross$-$validation relative error, commonly

abbreviated as xerror. Cross$-$validation is a statistical method used to

evaluate the predictive accuracy of a model by partitioning the original

data into a training set to train the model and a test set to evaluate it$.$ In

this context, the relative error, or xerror, measures the discrepancy

between the predicted and actual outcomes. Therefore, a classification

tree with the highest value of this cross$-$validation relative error is

considered to have the best performance because it indicates the

model's ability to generalize well to new, unseen data, thus making

accurate predictions.

A$.$ True

B$.$ False