A deicaset of $890$ cases was diviled into a training set of $500$ cases and a valldation set of $300$ cases. A classification algorithm, when trained on ithe:

training sot, yielded a misolassitcation error rate of $12\%$ on the validation data. Later, It was discovered that due to a mistake, $80$ cases from the

training set weic erronecusly duplicated and replaced $80$ cases in the valldation dataset. What is the revised miselassification error fate for the $220$

cases that were genuinely part of the validation data?

$(2$ marks$)$