varSelRFBoot
(Package: varSelRF) :
Bootstrap the variable selection procedure in varSelRF
Use the bootstrap to estimate the prediction error rate (wuth the .632+ rule) and the stability of the variable selection procedure implemented in varSelRF.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: varSelRFBoot
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randomVarImpsRF
(Package: varSelRF) :
Variable importances from random forest on permuted class labels
Return variable importances from random forests fitted to data sets like the original except class labels have been randomly permuted.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: randomVarImpsRF
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Plots of out-of-bag predictions and OOB error vs. number of variables.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: plot.varSelRFBoot
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Plot variable importances from random permutations of class labels and the variable importances from the original data set.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: randomVarImpsRFplot
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Plots a varSelRF object, showing the initial variable importances, and the change in OOB error with the number of variables.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: plot.varSelRF
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varSelRF
(Package: varSelRF) :
Variable selection from random forests using OOB error
Using the OOB error as minimization criterion, carry out variable elimination from random forest, by successively eliminating the least important variables (with importance as returned from random forest).
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: varSelRF
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varSelImpSpecRF
(Package: varSelRF) :
Variable selection using the "importance spectrum"
Perform variable selection based on a simple heuristic using the importance spectrum of the original data compared to the importance spectra from the same data with the class labels randomly permuted.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: varSelImpSpecRF
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selProbPlot
(Package: varSelRF) :
Selection probability plot for variable importance from random forests
Plot, for the top ranked k variables from the original sample, the probability that each of these variables is included among the top ranked k genes from the bootstrap samples.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: selProbPlot
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Returns error rate and stability measures of a varSelRFBoot object.
● Data Source:
CranContrib
● Keywords: classif, tree
● Alias: summary.varSelRFBoot
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