Timeline for When is a Model Underfitted?
Current License: CC BY-SA 3.0
6 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Jul 5, 2017 at 15:46 | comment | added | Sudip Bhandari | @FranckDernoncourt can we associate overfitting and underfitting to the size of training vs test data? Can we say that the model trained on smaller training set underfits? | |
| Jun 2, 2016 at 8:45 | comment | added | max | You seem to assume that the training error is a decent estimate of the bias. The bias (for the simple case of the MSE loss function) is defined as the expected error you make on the new data, when you average your prediction over all the different training sets. What makes J_train (not averaged out across training sets, and not using new data) a decent estimate of the bias? | |
| Jul 2, 2014 at 16:56 | comment | added | Franck Dernoncourt | @NeilSlater Thanks, good catch, there was indeed a typo :) | |
| Jul 2, 2014 at 16:55 | history | edited | Franck Dernoncourt | CC BY-SA 3.0 |
deleted 7 characters in body
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| Jul 2, 2014 at 10:24 | comment | added | Neil Slater | Did you mean to say "increase reduce the model complexity" on the last bullet point? I think just "increase the model complexity" . . . BTW good timing I am enrolled in that course and had only just watched the video you are referring to. | |
| Jun 29, 2014 at 23:14 | history | answered | Franck Dernoncourt | CC BY-SA 3.0 |