nmoorenz / rfUtilities

R package for random forests model selection, inference, evaluation and validation

rfUtilities (CRAN 2.1-5, development 2.2-0)

R package for random forests model selection, class balance and validation

Random Forests Model Selection, inference, fit and performance evaluation

rfUtilities 2.2-0 (GitHub development release)

• added ranger random forests implementation support

Available functions in rfUtilities 2.2-0 are:

	  accuracy - A function, called by the rf.crossValidation function or independently,     
                     that provides validation statistics for binomial or regression models
      
	  bivariate.partialDependence - Bivariate partial-dependency plot
	  
	  collinear - Evaluation of pair-wise linear or nonlinear correlations in data
      
	  logLoss - Calculates Logarithmic loss (logLoss)
      
	  multi.collinear - Multi-collinearity test with matrix permutation.
      
	  occurrence.threshold - A statistical sensitivity test for occurrence probability thresholds
      
	  probability.calibration - Isotonic probability calibration
      
	  rf.class.sensitivity - Random Forests class-level sensitivity analysis
      
	  rf.classBalance - Random Forests Class Balance (Zero Inflation Correction) Model
      
	  rf.combine - Combine Random Forests Ensembles
      
	  rf.crossValidation - Random Forests classification or regression cross-validation,
	                       simplified arguments and added ranger support
      
	  rf.effectSize - Random Forests parameter effect size
      
	  rf.imp.freq - Random Forests variable selection frequency
      
	  rf.modelSel - Random Forests Model Selection, simplified arguments and added ranger support
      
	  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 - Evaluates fit and overfit of random forests regression models
      
	  rf.significance - Significance test for classification or regression random forests models,
	                    simplified arguments and added ranger support
      
	  rf.unsupervised - Unsupervised Random Forests

Bugs: Users are encouraged to report bugs here. Go to issues in the menu above, and press new issue to start a new bug report, documentation correction or feature request. You can direct questions to [e-mail].

To install rfUtilities in R use install.packages() to download current stable release from CRAN

or, for the development version, run the following (requires the remotes package): remotes::install_github("jeffreyevans/rfUtilities")

Tutorial: See (http://evansmurphy.wixsite.com/evansspatial/random-forest-sdm).