This package is considered a duplicate. The official version of this package is found at:https://natydasilva.r-universe.dev/PPforest

Package: PPforest 0.2.0

Natalia da Silva

PPforest: Projection Pursuit Classification Forest

Implements projection pursuit forest algorithm for supervised classification.

Authors:Natalia da Silva [aut, cre], Dianne Cook [aut], Eun-Kyung Lee [aut]

# Install 'PPforest' in R:

install.packages('PPforest', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Uses libs:

Datasets:

On CRAN:

Last updated from:8ed790d18e. Checks:6 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	144
linux-devel-x86_64	OK	141
source / vignettes	OK	239
linux-release-arm64	OK	195
linux-release-x86_64	OK	150
wasm-release	OK	133

N. da Silva, D. Cook & E.K Lee

Last update: 2025-07-23
Started: 2017-12-15

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