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Aug 23, 2022 at 15:40 answer added Fred timeline score: 0
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Apr 4, 2017 at 14:22 history edited Berk U. CC BY-SA 3.0
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Sep 19, 2016 at 2:15 history edited Andre Silva CC BY-SA 3.0
removed tag as per meta post: http://meta.stats.stackexchange.com/questions/2804/what-should-the-best-practices-tag-be-for
Mar 13, 2016 at 21:23 history edited Berk U. CC BY-SA 3.0
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Feb 11, 2016 at 17:18 history edited Berk U. CC BY-SA 3.0
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S Jun 17, 2015 at 20:12 history edited AdamO
Adding "model selection" tag to the question.
S Jun 17, 2015 at 20:12 history suggested Kingz
Adding "model selection" tag to the question.
Jun 17, 2015 at 20:02 review Suggested edits
S Jun 17, 2015 at 20:12
Nov 5, 2014 at 16:59 answer added DataExplorer timeline score: 1
Mar 15, 2013 at 20:36 vote accept Berk U.
Mar 15, 2013 at 16:58 comment added Frank Harrell For 10-fold cv it is best to do $\geq 50$ repeats. More repeats will be needed with 5-fold. These are rules of thumb. A single 10-fold cv will given an unstable answer, i.e., repeat the 10 splits and you get enough of a different answer to worry.
Mar 15, 2013 at 14:47 comment added BGreene @Frank Harrell, why do you say 100 repetitions is necessary (I usually use 10 reps on 10 fold), is this a rule of thumb as the OP didn't give any specifics?
Mar 15, 2013 at 14:06 history edited user88 CC BY-SA 3.0
edited title
Mar 15, 2013 at 13:40 history tweeted twitter.com/#!/StackStats/status/312558816346648576
Mar 15, 2013 at 12:33 comment added Frank Harrell You will need to repeat 5-fold CV 100 times and average the results to get sufficient precision. And the answer from @bogdanovist is spot on. You can get the same precision of accuracy estimate from the bootstrap with fewer model fits.
Mar 15, 2013 at 12:22 answer added cbeleites timeline score: 46
Mar 15, 2013 at 11:13 comment added BGreene You might find the answers in the following question helpful: stats.stackexchange.com/questions/2306/…
Mar 15, 2013 at 2:53 answer added Bogdanovist timeline score: 356
Mar 15, 2013 at 2:21 history asked Berk U. CC BY-SA 3.0