# Projection Pursuit Classification Forest

## Documentation for package ‘PPforest’ version 0.2.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

baggtree | For each bootstrap sample grow a projection pursuit tree (PPtree object).
crab | Astralian crabs
fishcatch | Fish catch data set
glass | Glass data set
image | The image data set
leukemia | Leukemia data set
lymphoma | Lymphoma data set
NCI60 | NCI60 data set
node_data | Data structure with the projected and boundary by node and class.
olive | The olive data set
parkinson | Parkinson data set
permute_importance | Obtain the permuted importance variable measure
PPclassify | Predict class for the test set and calculate prediction error after finding the PPtree structure, .
PPforest | Projection Pursuit Random Forest
ppf_avg_imp | Global importance measure for a PPforest object as the average IMP PPtree measure over all the trees in the forest
ppf_global_imp | Global importance measure for a PPforest object
PPtree_split | Projection pursuit classification tree with random variable selection in each split
predict.PPforest | Predict method for PPforest objects
print.PPforest | Print PPforest object
ternary_str | Data structure with the projected and boundary by node and class.
trees_pred | Obtain predicted class for new data from baggtree function or PPforest
wine | Wine data set