Timeline for Comparison of Forecast Method for weather data, could I just use fitted curve or do I really need Out of Sample result?
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
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| Apr 23, 2021 at 11:49 | comment | added | Henry | Cross validation is not the same as curve fitting: models are fitted to the training data, and then assessed against the separated validation data, which allows choices between models and tuning of hyperparameters (e.g. dropping variables, regularisation or more) | |
| Apr 23, 2021 at 11:30 | comment | added | Iyo Widiastomo | Is cross validation is the same as curve fitting or in-sample fit or it is a different method from both in-sample and out of sample? | |
| Apr 22, 2021 at 8:50 | history | edited | Iyo Widiastomo | CC BY-SA 4.0 |
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| Apr 22, 2021 at 5:42 | answer | added | Stephan Kolassa | timeline score: 0 | |
| Apr 22, 2021 at 1:32 | answer | added | Tylerr | timeline score: 1 | |
| Apr 22, 2021 at 1:08 | comment | added | Henry | If you are trying to assess the potential accuracy of your model when predicting future weather, then testing it against out-of-sample test data is a good idea. If you are going to start by model selection and tuning, then (cross-)validation would be another useful tool too | |
| Apr 22, 2021 at 0:49 | history | asked | Iyo Widiastomo | CC BY-SA 4.0 |