| accuracy | Accuracy |
| bivariate.partialDependence | Bivariate partial-dependency plot |
| logLoss | Logarithmic loss (logLoss) |
| multi.collinear | Multi-collinearity test |
| occurrence.threshold | Test occurrence probability thresholds |
| plot.occurrence.threshold | Plot occurrence thresholds |
| plot.rf.cv | Plot random forests cross-validation |
| plot.rf.modelSel | Plot random forests model selection |
| plot.significance | Plot random forests significance |
| print.accuracy | Print accuracy |
| print.occurrence.threshold | Print occurrence.threshold |
| print.rf.cv | Print random forests cross-validation |
| print.rf.ensembles | Print for combined random forests ensembles |
| print.rf.modelSel | Print random forests model selection |
| print.significance | Print significance |
| probability.calibration | Isotonic probability calibration |
| rf.class.sensitivity | Random Forests class-level sensitivity analysis |
| rf.classBalance | Random Forest Class Balance (Zero Inflation Correction) Model |
| rf.combine | Combine Random Forests Ensembles |
| rf.crossValidation | Random Forest Classification or Regression Model Cross-validation |
| rf.effectSize | Random Forest effect size |
| rf.imp.freq | Random Forest variable selection frequency |
| rf.modelSel | Random Forest Model Selection |
| rf.partial.ci | Random Forests regression partial dependency plot with confidence intervals |
| rf.partial.prob | Random Forest probability scaled partial dependency plots |
| rf.regression.fit | Random Forest fit statistics |
| rf.significance | Random Forest model significance test |
| rf.unsupervised | Unsupervised Random Forests |
| rfu.news | rfUtilities news |
| summary.accuracy | Summarizing accuracy |
| summary.occurrence.threshold | Summarizing occurrence.threshold |
| summary.rf.cv | Summarizing cross-validation |
| summary.rf.ensembles | Summary for combined random forests ensembles |
| summary.rf.modelSel | Summarizing random forests model selection |
| summary.significance | Summarizing significance |