How to calculate the generalization error rate of a decision tree
<p>I'm doing the exercises of <em>Introduction to Data Mining</em>, and got stuck on following questions about decision tree:</p>

<p>Training
<a href="https://i.stack.imgur.com/Dw1Z4.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/Dw1Z4.png" alt="Training"></a></p>

<p>Testing
<a href="https://i.stack.imgur.com/lU7Qt.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/lU7Qt.png" alt="Testing"></a></p>

<p>Decision tree
<a href="https://i.stack.imgur.com/oMczN.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/oMczN.png" alt="Decision tree"></a></p>

<p>The question asks me to calculate generalization error rate by using optimistic and pessimistic approaches, and the answers are 0.3 and 0.5 respectively.
They are totally different from my answers 0.5 and  0.7. From my calculation, instances 3, 7, 8, 9, 10 are misclassifications.
I have searched many documentations on Google, and all of them didn't explain why and just showed that 3 / 10 = 0.3.
Please tell me what's the mistake I made, Thanks!</p>