Assertion: For implementing choose$-$attribute in DTL $($Decision Tree Learning$)$ algorithm, one exploits Information Theory to measure the expected amount of information provided by the attribute.

Reason: Information Theory provides a mathematical basis for measuring the information content.

Mark the correct choice as

A$.$ Both A and R are true and R is the correct explanation for A

B$.$ Both A and R are true but R is not the correct explanation for A

C$.$ A is True but R is False

D$.$ A is false but R is True