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rfUtilities (version 2.1-5)

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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install.packages('rfUtilities')

Monthly Downloads

148

Version

2.1-5

License

GPL-3

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Last Published

October 3rd, 2019

Functions in rfUtilities (2.1-5)

rf.class.sensitivity

Random Forests class-level sensitivity analysis
print.occurrence.threshold

Print occurrence.threshold
print.rf.cv

Print random forests cross-validation
multi.collinear

Multi-collinearity test
summary.accuracy

Summarizing accuracy
print.rf.modelSel

Print random forests model selection
rf.combine

Combine Random Forests Ensembles
rf.crossValidation

Random Forest Classification or Regression Model Cross-validation
print.rf.ensembles

Print for combined random forests ensembles
rfu.news

rfUtilities news
rf.classBalance

Random Forest Class Balance (Zero Inflation Correction) Model
print.significance

Print significance
probability.calibration

Isotonic probability calibration
rf.effectSize

Random Forest effect size
rf.modelSel

Random Forest Model Selection
rf.imp.freq

Random Forest variable selection frequency
rf.unsupervised

Unsupervised Random Forests
rf.significance

Random Forest model significance test
summary.significance

Summarizing significance
summary.rf.cv

Summarizing cross-validation
rf.partial.prob

Random Forest probability scaled partial dependency plots
rf.regression.fit

Random Forest fit statistics
summary.occurrence.threshold

Summarizing occurrence.threshold
rf.partial.ci

Random Forests regression partial dependency plot with confidence intervals
summary.rf.modelSel

Summarizing random forests model selection
summary.rf.ensembles

Summary for combined random forests ensembles
logLoss

Logarithmic loss (logLoss)
occurrence.threshold

Test occurrence probability thresholds
plot.occurrence.threshold

Plot occurrence thresholds
accuracy

Accuracy
plot.significance

Plot random forests significance
plot.rf.cv

Plot random forests cross-validation
plot.rf.modelSel

Plot random forests model selection
bivariate.partialDependence

Bivariate partial-dependency plot
print.accuracy

Print accuracy