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I think both of these methods will create a bias for certain values. i.e. if you the final subset does not meet the criteria, you remove a "bad" value (an outlier) and replace it with a "good" value. This will result in "good" values being used more often and "bad" values being used less often.

Preston S
– Preston S

2014-09-30 15:06:48 +00:00
Commented Sep 30, 2014 at 15:06
@PrestonS - So what? This comment of yours suggests you have some addition requirements that you have not yet told us.

David Hammen
– David Hammen

2014-09-30 15:19:55 +00:00
Commented Sep 30, 2014 at 15:19
@DavidHammen No, I specified random which means an even distribution across all possible values. Swapping out values in this way is definitely not random.

Preston S
– Preston S

2014-09-30 15:23:53 +00:00
Commented Sep 30, 2014 at 15:23
What does that even mean, Preston? You have not fully specified the problem.

David Hammen
– David Hammen

2014-09-30 15:40:23 +00:00
Commented Sep 30, 2014 at 15:40
@DavidHammen It means I'm looking for an algorithm to produce one subset that fulfills my criteria. Then, if I ran the algorithm many times, it would eventually have returned all the possible subsets an equal amount of times.

Preston S
– Preston S

2014-09-30 15:50:12 +00:00
Commented Sep 30, 2014 at 15:50

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