Timeline for Significance testing of cross-validated classification accuracy: shuffling vs. binomial test
Current License: CC BY-SA 3.0
10 events
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| Apr 13, 2017 at 12:44 | history | edited | CommunityBot |
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| Jun 11, 2014 at 11:56 | vote | accept | amoeba | ||
| Mar 6, 2014 at 23:52 | comment | added | amoeba | @cbeleites: To test significance with the binomial confidence interval is of course equivalent to binomial testing. In my update I was referring to the confidence interval that one would try to construct from iterations of CV (even though I am not sure how to do it correctly in case of Monte Carlo CV that I described)... Anyway, please see the reply to this question that I just posted, I provided a very simple simulation there that I hope illustrates my observations. | |
| Mar 6, 2014 at 23:47 | answer | added | amoeba | timeline score: 2 | |
| Mar 6, 2014 at 20:50 | comment | added | cbeleites | I don't see how the confidence interval approach is that distinct from the binomial testing: if you believe your random variable to be binomially distributed you'd also construct a binomial c.i. - but that would throw you back to the same problem, woudn't it? | |
| Mar 5, 2014 at 22:55 | comment | added | amoeba | What seems to be a very relevant paper: Permutation Tests for Classification. | |
| Mar 5, 2014 at 19:19 | answer | added | julieth | timeline score: 2 | |
| Mar 5, 2014 at 18:01 | comment | added | amoeba | Related thread: How to assess statistical significance of the accuracy of a classifier? | |
| Mar 5, 2014 at 14:50 | history | edited | amoeba | CC BY-SA 3.0 |
updated
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| Mar 5, 2014 at 0:04 | history | asked | amoeba | CC BY-SA 3.0 |