Chidi Nweke
05/23/2023, 8:53 AMy_t = y_t-1
but for y_t = t-t-n
? This is particularly important because we essentially have multiple tasks, forecasting say 1 week, 2 weeks, 3 weeks into the future and we assume that after the following week we will observe the next value. From what I understood from reading the docs in its entirety the forecast
method in Naive would not achieve this as it only looks at your training data.Rafael Correia Da Silva
05/23/2023, 12:02 PMcross_validation
method from the core neuralforecast can help?
it basically trains your model up to a point then forecast for a given number of horizons in the future, which could be week 1, 2, .., nChidi Nweke
05/23/2023, 12:14 PMRafael Correia Da Silva
05/23/2023, 12:18 PMChidi Nweke
05/23/2023, 12:19 PMforward
method. I'd expect to be able to find the optimized alpha value on the training set and then call forward on the test set. Being able to use y_true in a rolling way is a big requirement for meRafael Correia Da Silva
05/23/2023, 12:35 PMChidi Nweke
05/23/2023, 12:39 PMRafael Correia Da Silva
05/23/2023, 12:44 PMChidi Nweke
05/23/2023, 12:50 PMRafael Correia Da Silva
05/23/2023, 12:50 PMChidi Nweke
05/23/2023, 12:52 PMRafael Correia Da Silva
05/23/2023, 12:52 PMrolling
flag in cross_validation
to do just that