# Projection Pursuit Classification Forest

## Documentation for package ‘PPforest’ version 0.1.2

- DESCRIPTION file.
- User guides, package vignettes and other documentation.

## 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 This dataset comes from a study of gene expression in two types of acute leukemias, acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML). Gene expression levels were measured using Affymetrix high density oligonucleotide arrays containing 6817 human genes. A data set containing 72 observations from 3 leukemia types classes. • Type has 3 classes with 38 cases of B-cell ALL, 25 cases of AML and 9 cases of T-cell ALL. • Gene1 to Gen 40 gene expression levels

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
PPclassify2 | 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
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