Timeline for R time-series forecasting with neural network, auto.arima and ets
Current License: CC BY-SA 4.0
7 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Aug 28, 2019 at 10:43 | comment | added | Komal Batool | The question was how can ANN be compared with statistical models like ARIMA (since these models are compared using their AIC values) and the answer is using other statistical values like MAE or RMSE which can be obtained by accuracy() function. There is no point of confusion in it. | |
| Aug 28, 2019 at 9:51 | comment | added | mkt | That is helpful to know. But my point is that this is not a site about coding, even though code can certainly illuminate questions and answers. And so your answer would be better if you highlighted the substantive issue. | |
| Aug 28, 2019 at 9:46 | comment | added | Komal Batool | when you use function accuracy(model), it gives certain statistics like ME, MAE, RMSE, MPE and so on. You can use any of them or all to compare two or more models. Say for instance, model with least RMSE(Root Mean Square Error) is considered as the best model among all. | |
| Aug 28, 2019 at 7:04 | comment | added | mkt | I had to read this a couple of times to get your point. While the naming of the variables is good coding practice, it's not central to the answer. The main part of your answer is in the final line (using MAE, etc). If you could highlight (or even better, expand on) that, it would improve this. | |
| Aug 28, 2019 at 6:50 | review | Late answers | |||
| Aug 28, 2019 at 7:04 | |||||
| Aug 28, 2019 at 6:35 | review | First posts | |||
| Aug 28, 2019 at 8:20 | |||||
| Aug 28, 2019 at 6:32 | history | answered | Komal Batool | CC BY-SA 4.0 |