error in featureFiltering with small variable count

[minemR]

I got error:

Error in .local(.Object, ...) : 
  user cannot request for more solutions than is possible given the data set

Code:

train_df <- sim_data(n = 1000,
                     modelvars = 10,
                     noisevars = 10,
                     model_sd = 4,
                     noise_sd = 4,
                     epsilon_sd = 4,
                     outcome = "regression",
                     cutoff = NULL)
head(train_df[, 1:10])
# Maximum Relevance Minimum Redundancy Filter
test_mr <- featureFiltering(data = train_df,
                            target = "y",
                            method = "mrmr",
                            returning = "names")

[cosmin-novac]

Did you manage to get around this?

I found a hacky workaround by adding method="bootstrap" to the internal mRMR.ensemble function call. This performs the classical mRMR feature selection on several bootrstap selections of the dataset instead of using the whole dataset, which the default method="exhaustive" would have done.