Table 1.

Method overview

Command	Parameters	Information
ensemble_fs	data	object of class data.frame
	classnumber	index of variable for binary classification
	NA_threshold	threshold for deletion of features with a greater proportion of NAs
	cor_threshold	correlation threshold within features
	runs	amount of runs for randomForest and cforest
	selection	selection of feature selection methods to be conducted
barplot_fs	name	character string giving the name of the file
	efs_table	table object of class matrix retrieved from ensemble_fs
efs_eval	data	object of class data.frame
	efs_table	table object of class matrix retrieved from ensemble_fs
	file_name	character string, name which is used for the two possible PDF files.
	classnumber	index of variable for binary classification
	NA_threshold	threshold for deletion of features with a greater proportion of NAs
	logreg	logical value indicating whether to conduct an evaluation via logistic regression or not
	permutation	logical value indicating whether to conduct a permutation of the class variable or not
	p_num	number of permutations; default set to a 100
	variances	logical value indicating whether to calculate the variances of importances retrieved
		from bootstrapping or not
	jaccard	logical value indicating whether to calculate the Jaccard-index or not
	bs_num	number of bootstrap permutations of the importances
	bs_percentage	proportion of randomly selected samples for bootstrapping

The R-package EFS provides three functions