Random Forests Model Selection and Performance Evaluation

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.classBalance | Random Forest Class Balance (Zero Inflation Correction) Model |

rf.class.sensitivity | Random Forests class-level sensitivity analysis |

rf.combine | Combine Random Forests Ensembles |

rf.crossValidation | Random Forest Classification or Regression Model... |

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... |

rf.partial.prob | Random Forest probability scaled partial dependency plots |

rf.regression.fit | Random Forest fit statistics |

rf.significance | Random Forest model significance test |

rfu.news | rfUtilities news |

rf.unsupervised | Unsupervised Random Forests |

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 |

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