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Important question : may you clarify if you using some special algorithms for generation many test data / train data splits
to get big difference between splits since some splits many have negligible difference for example for
samples 1 2 3 4 5 6 7 8 9 10 11 12 good split test data 1 2 3 4 5 6 train data 7 8 9 10 11 12 test data 1 2 3 7 8 9 train data 4 5 6 10 11 12 minimum difference between all sets is 3
bad split test data 1 2 3 4 5 6 train data 7 8 9 10 11 12 test data 1 2 3 4 5 7 train data 6 8 9 10 11 12 minimum difference between all sets 1
The text was updated successfully, but these errors were encountered:
my guess here d_test_list[[i]] <- d1_test[sample(1:nrow(d1_test), size_test),]
subsamples are generated many times with small difference?
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yes, those are random samples, with relatively large sample sizes those idiosyncrasies do not matter
I see thanks, but my guess , you only assuming this and not tested it by experiment
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Important question :
may you clarify if you using some special algorithms for generation many test data / train data splits
to get big difference between splits
since some splits many have negligible difference for example for
samples 1 2 3 4 5 6 7 8 9 10 11 12
good split
test data 1 2 3 4 5 6 train data 7 8 9 10 11 12
test data 1 2 3 7 8 9 train data 4 5 6 10 11 12
minimum difference between all sets is 3
bad split
test data 1 2 3 4 5 6 train data 7 8 9 10 11 12
test data 1 2 3 4 5 7 train data 6 8 9 10 11 12
minimum difference between all sets 1
The text was updated successfully, but these errors were encountered: