Timeline for Is an overfitted model necessarily useless?
Current License: CC BY-SA 3.0
8 events
| when toggle format | what | by | license | comment | |
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| Oct 6, 2019 at 8:20 | comment | added | Hossein | I just did here is the link | |
| Oct 6, 2019 at 7:53 | comment | added | Richard Hardy | @Breeze, I think you could ask this on a separate thread (and link to this one for context if needed). | |
| Oct 6, 2019 at 5:57 | comment | added | Hossein | Is it ever possible for a model to attain 100% accuracy on both train and test and has no overifitted ? | |
| May 11, 2017 at 17:16 | history | edited | Richard Hardy | CC BY-SA 3.0 |
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| May 11, 2017 at 17:04 | comment | added | Henry |
You asked for an example: take the code for a neural net on the iris dataset at stats.stackexchange.com/a/273930/2958 and then try with set.seed(100) for an illustration like the phenomenon described here and set.seed(15) for the opposite. Perhaps better to say "an indicator of possible overfitting"
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| May 11, 2017 at 14:34 | history | edited | Richard Hardy | CC BY-SA 3.0 |
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| May 11, 2017 at 11:44 | vote | accept | Hossein | ||
| May 11, 2017 at 11:28 | history | answered | Richard Hardy | CC BY-SA 3.0 |