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rfPermute

Estimate Permutation p-Values for Random Forest Importance Metrics

Estimate significance of importance metrics for a Random Forest model by permuting the response variable. Produces null distribution of importance metrics for each predictor variable and p-value of observed. Provides summary and visualization functions for 'randomForest' results.

Functions (21)

casePredictions

Case Predictions

classConfInt

Classification Confidence Intervals

cleanRFdata

Clean Random Forest Input Data

confusionMatrix

Confusion Matrix

exptdErrRate

Expected Error Rate

impHeatmap

Importance Heatmap

pctCorrect

Percent Correctly Classified

plot.rp.importance

Plot Random Forest Importance Distributions

plotConfMat

Plot Confusion Matrix

plotImpVarDist

Plot Important Variable Distribution

plotInbag

Plot inbag distribution

plotNull

Plot Random Forest Importance Null Distributions

plotOOBtimes

Plot Times OOB

plotPredictedProbs

Plot Predicted Probabilities

plotRFtrace

OOB Trace

plotVotes

Plot Vote Distribution

proximityPlot

Plot Random Forest Proximity Scores

rfPermute

Estimate Permutation p-values for Random Forest Importance Metrics

rp.combine

Combine rfPermute Objects

rp.importance

Extract rfPermute Importance Scores and p-values.

symb.metab

Symbiodinium type metabolite profiles

rfPermute

Estimate Permutation p-Values for Random Forest Importance Metrics

v2.1.81
GPL (>= 2)
Authors
Eric Archer [aut, cre]
Initial release

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