Table 2.

Parameters used in each method.

	Parameters
Feature selection algorithm
Boruta	Default parameters
Recursive feature elimination	{functions: rfFuncs, method: repeatedcv, repeats: 5, verbose: FALSE}
Algorithm
Random forests	{n_estimators: 100, criterion: gini, min_samples_split: 2, max_features: auto}
Decision trees	Default parameters, {criterion: gini, splitter: best, min_samples_split: 2}
Logistic regression	Default parameters, {family: binomial}
Support vector machine (SVM)	{kernel: linear, gamma: (depends on the data) (between 0.000001 and 0.1), cost: (depends on the data) (between 0.1 and 10)}