# How to create a confusion matrix for one node of a decision tree?

I am doing past papers for my data science exam and was curious about one of the questions. They ask us to create a confusion matrix by hand for one node of a decision tree.

I understand how to create a decision tree for an entire model, but I am unsure on how to create one for just one variable. Should the entire first row be 0s other than the class A as it should always predict class A or am I missing something.

I have attached the decision tree and the exact wording of the question below. Thanks!

"(iv) Present a confusion matrix for the [leftmost terminal] node."

• If the tree had only one node, what would you do? Do same for that node, as if it is the only node May 4 at 15:19
• At least this is what I gather from the phrasing of the question. Unless there have been previous questions which follow another route, which would clarify this question further May 4 at 16:01
• I don't think the other questions are related so I believe 10xAI must be what they are asking for. Thanks! May 4 at 16:53

Below should be the CM - Rows are "True" and the Column is the "Predicted" $$\begin{array} {|r|r|} \hline &A &B &C &D &E &F \\ \hline A &62 &- &- &- &- &- \\ \hline B &21 &- &- &- &- &- \\ \hline C &13 &- &- &- &- &- \\ \hline D &00 &- &- &- &- &- \\ \hline E &02 &- &- &- &- &- \\ \hline F &02 &- &- &- &- &- \\ \hline \end{array}$$