cvRFBORUTA: Crossvalidation for Random Forests with Boruta feature...
In bootfs: Derive Robust Feature Sets for Two or Multiclass Classification Problems

Description Usage Arguments Details Value Author(s) References See Also Examples

Main Wrapper for the Random Forest/Boruta crossvalidation.

cvRFBORUTA(logX, groupings, DIR, params = NULL)

`logX`	The data matrix. Samples in rows, features in columns.
`groupings`	A list of group vectors. Each list element is a named vector (length equals the number of samples), holding group assignments for each sample (either 1 for group A and -1 for group B).
`DIR`	The output base directory.
`params`	A parameter list with the following elements. `seed`: a random seed. `ncv`: the number of folds in the crossvalidation. `repeats`: number of repeats of the CV. `maxRuns`: Boruta parameter. `rfimportance` Which importance measure to use in the random forest feature ranking. `ntree` Number of trees in the random forest. `localImp` Local importance in random forest. `fs.method` Either `rf` or `rf_boruta`. `saveres` Boolean, if TRUE, save results.

Do a ncv-fold crossvalidation (CV) with repeats repeats. Each grouping assignment from groupings will be used as classification task. If more than one grouping is present, the package uses parallelisation in the package multicore.

This function is usually called by doCV.

CV result. A list with three elements res, featlist and performance, holding the crossvalidation data, an extracted features list in each cv-iteration and an overall performance object, holding information on the performance (AUC values and a roc curve object that can be plotted). See resultCV for making a summary plot for the CV.

Christian Bender

Miron B. Kursa, Witold R. Rudnicki (2010). Feature Selection with the Boruta Package. Journal of Statistical Software, 36(11), p. 1-13. URL: http://www.jstatsoft.org/v36/i11/

Breiman, L. (2001), _Random Forests_, Machine Learning 45(1), 5-32.

Breiman, L (2002), “Manual On Setting Up, Using, And Understanding Random Forests V3.1”, <URL:http://oz.berkeley.edu/users/breiman/Using_random_forests_V3.1.pdf>.

doCV Help of Boruta package.