20.26 Decision Tree Performance

Here we plot the performance of the decision tree, showing a risk chart. The areas under the recall and risk curves are also reported.

predict_te <- predict(model, ds[te, vars], type="prob")[,2]
riskchart(predict_te, actual_te, risk_te)

An error matrix shows, clockwise from the top left, the percentages of true negatives, false positives, true positives, and false negatives.

predict_te <- predict(model, ds[te, vars], type="class")
sum(actual_te != predict_te)/length(predict_te) # Overall error rate

## [1] 0.1664365

actual_te %>%
  table(predict_te, dnn=c("Actual", "Predicted")) %>%
  '*'(100/(length(predict_te))) %>%
  round()

##       Predicted
## Actual No Yes
##    No  75   3
##    Yes 13   8

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