# Randomer Forest

## Documentation for package ‘rerf’ version 2.0.4

- DESCRIPTION file.

## Help Pages

BICCutFast | Find minimizing BIC Cut for Vector
BICCutMclust | Find minimizing BIC Cut for Vector
BuildTree | RerF Tree Generator
checkInputMatrix | Determine if given input can be processed by Urerf.
ComputeSimilarity | Compute Similarities
FeatureImportance | Compute Feature Importance of a RerF model
flipWeights | Change the sign of the weights
getFeatures | Extract feature indicies from the sparse projection vector.
getWeights | Extract feature weights from the sparse projection vector.
GrowUnsupervisedForest | Creates Urerf Tree.
makeA | Create rotation matrix used to determine mtry features.
makeAB | Create rotation matrix used to determine linear combination of mtry features.
mnist | A subset of the MNIST dataset for handwritten digit classification
OOBPredict | Compute out-of-bag predictions
PackForest | Packs a forest and saves modified forest to disk for use by PackPredict function
PackPredict | Compute class predictions for each observation in X
Predict | Compute class predictions for each observation in X
PrintTree | RerF Tree Printer
RandMatBinary | Create a Random Matrix: Binary
RandMatContinuous | Create a Random Matrix: Continuous
RandMatCustom | Create a Random Matrix: custom
RandMatFRC | Create a Random Matrix: FRC
RandMatFRCN | Create a Random Matrix: FRCN
RandMatImageControl | Create a Random Matrix: image-control
RandMatImagePatch | Create a Random Matrix: image-patch
RandMatPoisson | Create a Random Matrix: Poisson
RandMatRF | Create a Random Matrix: Random Forest (RF)
RandMatTSpatch | Create a Random Matrix: ts-patch
RerF | RerF forest Generator
RunFeatureImportance | Compute Feature Importance of a single RerF tree
RunFeatureImportanceBinary | Compute Feature Importance of a single RerF tree
RunFeatureImportanceCounts | Tabulate the unique feature combinations used in a single RerF tree
RunOOB | Predict class labels on out-of-bag observations using a single tree.
RunPredict | Predict class labels on a test set using a single tree.
RunPredictLeaf | Calculate similarity using a single tree.
StrCorr | Compute tree strength and correlation
TwoMeansCut | Find minimizing Two Means Cut for Vector
uniqueByEquivalenceClass | Remove unique projections that are equivalent due to a rotation of 180 degrees.
Urerf | Unsupervised RerF forest Generator