Examples of FFTs with FFTrees | Mushrooms data | Creating FFTs | Visualizing cue accuracies | Visualizing FFT performance | Trading off prediction errors | An alternative FFT | Iris.v data | Viewing alternative FFTs | Titanic data | Vignettes | References

1. Using my.tree | Verbally defining FFTs | Example | Inspect FFTrees object: | Creating an alternative FFT | Visualize FFT: | FFT definition: | Note the flipped direction value for 2nd cue (exit = '0'): | 'if (cp = a), predict 1' in the tree definition corresponds to | 'if (cp != a), predict 0' in the my.tree description and plot. | 2. Using tree.definitions | Overview: Retrieving, manipulating, and using FFT definitions | Obtaining individual tree definitions | Manipulating individual tree definitions | Using magrittr pipes to combine steps | Re-converting and collecting sets of tree definitions | Applying sets of tree definitions to data | Details | Vignettes

Visualizing FFTrees | The Titanic data | Visualising cue accuracies | Additional arguments | Plotting performance for new data | Vignettes

Step\ 1: Install and load the FFTrees package | Step\ 2: Create FFTs from training data (and test on testing data) | Other arguments | Step\ 3: Inspect and summarize FFTs | Step\ 4: Visualise the final FFT | Advanced functions | Accessing outputs | Predicting for new data | Directly defining FFTs | Vignettes | References

What is a pirateplot()? | Main arguments | Themes | Theme 1 | Theme 2 | Theme 3 | Theme 4 | Theme 0 | Color palettes | Customising elements | Additional arguments | Multiple IVs | beside = FALSE | Output | Specifying individual point parameters | References

YaRrr! The pirate's guide to R | Guides | Examples | pirateplot() | piratepal() | Questions | References

Accuracy Statistics in FFTrees | Conditional accuracy statistics | Aggregate accuracy statistics | Speed and frugality statistics | Additional measures | Vignettes | References

Details on the FFTrees() function | Example: Predicting heart disease | Creating trees with FFTrees() | Elements of an FFTrees object | Basic performance characteristics of FFTs | Cue performance information | Tree definitions | Accuracy statistics of FFTs | Classification decisions | Predicting new cases with predict() | Visualising trees | Manually defining an FFT | Vignettes | References

Fast-and-Frugal Trees (FFTs) | Using the FFTrees package | Getting started | Vignettes | Datasets | Details about the datasets | Citing FFTrees | Contact | Bibliography

piratepal() | Examples | Plotting the Up house | Have a favorite palette?