A fast and frugal tree classifier for sklearn
A fast-and-frugal-tree classifier based on Python's scikit learn.
Fast-and-frugal trees are classification trees that are especially useful for making decisions under uncertainty. Due their simplicity and transparency they are very robust against noise and errors in data. They are one of the heuristics proposed by Gerd Gigerenzer in Fast and Frugal Heuristics in Medical Decision. This particular implementation is based on on the R package FFTrees, developed by Phillips, Neth, Woike and Grassmaier.
You can install fasttrees using
pip install fasttrees
Instantiate a fast-and-frugal tree classifier:
fc = FastFrugalTreeClassifier()
Fit on your data:
View the fitted tree (this is especially useful if the 'predictions' will be carried out by humans in practice):
preds = fc.predict(X_test)
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size fasttrees-1.2.2.tar.gz (5.0 kB)||File type Source||Python version None||Upload date||Hashes View hashes|