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Mar 30, 2023 at 11:23 vote accept M.G.Poirot
Mar 22, 2023 at 1:16 history edited M.G.Poirot CC BY-SA 4.0
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Mar 21, 2023 at 18:49 history edited M.G.Poirot CC BY-SA 4.0
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Mar 21, 2023 at 18:35 history edited M.G.Poirot CC BY-SA 4.0
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Mar 21, 2023 at 17:27 history edited M.G.Poirot CC BY-SA 4.0
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Mar 21, 2023 at 17:22 history edited M.G.Poirot CC BY-SA 4.0
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Mar 21, 2023 at 17:00 history edited Sycorax CC BY-SA 4.0
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S Mar 21, 2023 at 15:11 history bounty ended M.G.Poirot
S Mar 21, 2023 at 15:11 history notice removed M.G.Poirot
Mar 20, 2023 at 17:00 history edited Firebug CC BY-SA 4.0
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Mar 20, 2023 at 10:35 answer added Firebug timeline score: 1
Mar 20, 2023 at 10:23 comment added Firebug See this answer stats.stackexchange.com/a/536162/60613
Mar 20, 2023 at 0:11 comment added M.G.Poirot Not at all: it does neither touch upon statistical testing nor MCC. In addition, as opposed to this question, the crux of that question is on the "nested" part of a CV-scheme, which is not a part of this question.
Mar 18, 2023 at 19:06 comment added David B Ok, then it seems like your question is a duplicate of stats.stackexchange.com/questions/250282/…. Is your question answered there?
Mar 18, 2023 at 16:58 comment added M.G.Poirot It is not nested, it is simply 5-fold, 5-repeat CV, literally the most simple output of sklearn.model_selection.RepeatedKFold: Thus, performance_model_A is an 1D array of length n_splits × n_folds.
Mar 18, 2023 at 13:17 comment added David B Can you give more detail on your CV procedure? Is it nested CV? For example, with 5 splits, is it 5-fold CV, or do you hold-out 1/5th of the data, train (with some unspecified amount of CV) in the remaining 4/5th, and then test in the held-out 1/5th?
S Mar 18, 2023 at 10:57 history bounty started M.G.Poirot
S Mar 18, 2023 at 10:57 history notice added M.G.Poirot Authoritative reference needed
Mar 18, 2023 at 10:54 history edited M.G.Poirot CC BY-SA 4.0
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Mar 16, 2023 at 16:53 answer added cbeleites timeline score: 4
Mar 15, 2023 at 20:26 history asked M.G.Poirot CC BY-SA 4.0