The Confusion matrix shows how well the tree separates the classes correctly
using these metrics:

True positive rate (TPR) — the
probability that an event case is predicted correctly

False positive rate (FPR) —
the probability that a nonevent case is predicted incorrectly

False negative rate (FNR) —
the probability that an event case is predicted incorrectly

True negative rate (TNR) — the
probability that a nonevent case is predicted correctly

Interpretation

A low value for % Correct is usually due to a deficient fitted model.
Various problems lead to a deficient model. If the % Correct is very low,
consider whether to modify the minimum number of cases to split an internal
node or to change the number of predictors that the analysis considers for
splitting a node.

By using this site you agree to the use of cookies for analytics and personalized content. Read our policy