rofi: Repeated Optimized Feature Integration
In pmartR/peppuR:

Repeated Optimized Feature Integration

rofi(MLinput, source_alg_pairs, nn = 1, f_prob = 0.1, nu = 1/100,
  max_iter = 2 * sum(attr(MLinput, "data_info")$number_of_features),
  conv_check = (sum(attr(MLinput, "data_info")$number_of_features) + 1),
  epsilon = 0.01, after_conv_checks = 100)

`MLinput`	an as.MLinput object which contains a single X data frame or a list of X data frames, a Y data frame and attributes
`source_alg_pairs`	a named vector of algorithms (one of "knn", "nb", "svm", or "rf") with names as the corresponding data source
`nn`	integer. The number of times to repeat the optimization in its entirety
`f_prob`	numeric greater than 0 and leq 1. The proportion of the full feature set to initialize the optimization routine
`nu`	numeric greater than 0 and leq 1. The scale value for feature acceptance criteria of a difference in AUC values
`max_iter`	int. Maximum number of iterations to allow in nn iterations
`conv_check`	int. Number of iterations at which to perform a convergence check. Typically set to the total number of features
`epsilon`	numeric greater than 0 and leq 1. AUC convergence threshold, typically small (< 0.1).
`after_conv_checks`	int. After the initial convergence check, the Interval of iterations at which to perform a convergence check