20.64 Conditional 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.

predicted <- predict(model, ds[te, vars], type="prob")[,2]
riskchart(predicted, 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.

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

## [1] 0.1535953

round(100*table(actual_te, predicted, dnn=c("Actual", "Predicted"))/length(predicted))

##       Predicted
## Actual No Yes
##    No  74   4
##    Yes 11  10

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