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rfUtilities (version 2.1-3)

Random Forests Model Selection and Performance Evaluation

Description

Utilities for Random Forest model selection, class balance correction, significance test, cross validation and partial dependency plots.

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Version

Install

install.packages('rfUtilities')

Monthly Downloads

109

Version

2.1-3

License

GPL-3

Maintainer

Jeffrey S Evans

Last Published

February 21st, 2018

Functions in rfUtilities (2.1-3)

accuracy

Accuracy

rf.unsupervised

Unsupervised Random Forests

rf.significance

Random Forest model significance test

summary.rf.ensembles

Summary for combined random forests ensembles

summary.rf.modelSel

Summarizing random forests model selection

occurrence.threshold

Test occurrence probability thresholds

plot.occurrence.threshold

Plot occurrence thresholds

print.rf.modelSel

Print random forests model selection

print.rf.ensembles

Print for combined random forests ensembles

summary.occurrence.threshold

Summarizing occurrence.threshold

summary.rf.cv

Summarizing cross-validation

plot.rf.cv

Plot random forests cross-validation

plot.rf.modelSel

Plot random forests model selection

print.accuracy

Print accuracy

plot.significance

Plot random forests significance

rf.classBalance

Random Forest Class Balance (Zero Inflation Correction) Model

rf.class.sensitivity

Random Forests class-level sensitivity analysis

rf.partial.prob

Random Forest probability scaled partial dependency plots

rf.regression.fit

Random Forest fit statistics

summary.significance

Summarizing significance

print.occurrence.threshold

Print occurrence.threshold

logLoss

Logarithmic loss (logLoss)

multi.collinear

Multi-collinearity test

print.rf.cv

Print random forests cross-validation

rf.modelSel

Random Forest Model Selection

rf.partial.ci

Random Forests regression partial dependency plot with confidence intervals

print.significance

Print significance

rf.effectSize

Random Forest effect size

probability.calibration

Isotonic probability calibration

rf.imp.freq

Random Forest variable selection frequency

bivariate.partialDependence

Bivariate partial-dependency plot

rf.combine

Combine Random Forests Ensembles

rf.crossValidation

Random Forest Classification or Regression Model Cross-validation