Go to TogaWare.com Home Page. Data Science Desktop Survival Guide
by Graham Williams
Duck Duck Go


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] 0.1616943

actual_te %>%
  table(predict_te, dnn=c("Actual", "Predicted")) %>%
  '*'(100/(length(predict_te))) %>%
##       Predicted
## Actual No Yes
##    No  77   3
##    Yes 13   7

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Other online resources include the GNU/Linux Desktop Survival Guide.
Books available on Amazon include Data Mining with Rattle and Essentials of Data Science.
Popular open source software includes rattle and wajig.
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