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Performance Vector of Decision Trees

User: "auxilium"
New Altair Community Member
Updated by Jocelyn
Hello,

I think I've some understanding problems regarding the performance vector of a decision tree.

I've a  training data set with 16 records, which are categorized negative or positive.
I created a process and rapidminer created a new decision tree, which classifies each record correctly. ( I even checked every record manually by myself.)
Now I'd like the system to check the performance, so i added a "nominal cross validation".

Then the system reproduces the same decision, but the performance vector of this tree says, that both recall and precision are not 100%.

What's the reason for it?

I've checked the dataset manually and the decision tree seems to be allright for that specific dataset. But If i used this validation function, it says it's not?

I'dont understand this atm.

Would you be so nice and try to explain it to me?

Regards

auxilium

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