# Oblique Decision Random Forest for Classification and Regression

## Documentation for package ‘ODRF’ version 0.0.5

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

## Help Pages

Accuracy | accuracy of oblique decision random forest
as.party.ODT | 'ODT' as 'party'
best.cut.node | find best splitting variable and node
defaults | Default values passed to RotMat*
ODBT | Classification and Regression using the Ensemble of ODT-based Boosting Trees
ODBT.default | Classification and Regression using the Ensemble of ODT-based Boosting Trees
ODBT.formula | Classification and Regression using the Ensemble of ODT-based Boosting Trees
ODRF | Classification and Regression using Oblique Decision Random Forest
ODRF.default | Classification and Regression using Oblique Decision Random Forest
ODRF.formula | Classification and Regression using Oblique Decision Random Forest
ODT | Classification and Regression with Oblique Decision Tree
ODT.default | Classification and Regression with Oblique Decision Tree
ODT.formula | Classification and Regression with Oblique Decision Tree
online.ODRF | using new training data to update an existing 'ODRF'.
online.ODT | using new training data to update an existing 'ODT'.
plot.Accuracy | plot method for 'Accuracy' objects
plot.ODT | to plot an oblique decision tree
plot.prune.ODT | to plot pruned oblique decision tree
plot.VarImp | Variable Importance Plot
plot_ODT_depth | plot oblique decision tree depth
PPO | Projection Pursuit Optimization
predict.ODRF | predict based on an ODRF object
predict.ODT | making predict based on ODT objects
print.ODRF | print ODRF
print.ODT | print ODT result
prune.ODRF | Pruning of class 'ODRF'.
prune.ODT | pruning of class 'ODT'
RandRot | Samples a p x p uniformly random rotation matrix
RotMatMake | Create rotation matrix used to determine the linear combination of features.
RotMatPPO | Create a Projection Matrix: RotMatPPO
RotMatRand | Random Rotation Matrix
RotMatRF | Create a Projection Matrix: Random Forest (RF)
VarImp | Extract variable importance measure