select best indices from the result of ensemble using mRMR - r

Question

I am using the R package mRMRe for feature selection and trying to get the indices of most common feature from the results of ensemble:
ensemble <- mRMR.ensemble(data = dd, target_indices = target_idx,solution_count = 5, feature_count = 30)
features_indices = as.data.frame(solutions(ensemble))
This give me the below data:
MR_1 MR_2 MR_3 MR_4 MR_5
2793 2794 2796 2795 2918
1406 1406 1406 1406 1406
2798 2800 2798 2798 2907
2907 2907 2907 2907 2800
2709 2709 2709 2709 2709
1350 2781 1582 1350 1582
2781 1350 2781 2781 636
2712 2712 2712 2712 2781
636 636 636 636 2779
2067 2067 2067 2067 2712
2328 2328 2357 2357 2067
2357 783 2328 2328 2328
772 2357 772 772 772
I want to use some sort of voting logic to select the most frequent index for each row across all columns.
For example in the above image :
1. For the first row there is no match - so select the first one.
2. There are some rows where min occurrence is 2 - so select that one.
3. In case of tie - check if any occurs thrice, if yes select that one, or else from the tied indices select the first occurring one.
May be I am making it too complex, but basically I want to select best indices from all the indices for each row from the dataframe.
Can someone please help me on this?

Answer 1

Here's a simple solution using apply:
apply(df, 1, function(x) { names(which.max(table(x))) })
which gives:
[1] "2793" "1406" "2798" "2907" "2709" "1350" "2781" "2712" "636" "2067" "2328" "2328" "772"
For each row, the function table counts occurrences of each unique element, then we return the name of the element with the maximum number of occurrences (if there is a tie, the first one is selected).