Hello Community,
I got 5 years (2014-2018) of monthly sales data on a specific product. I would like to build 12 Random forest models to predict each month of the year 2018.
1. Model to predict January 2018
2. Model to predict Feburay 2018
...
12. Model to predict December 2018.
So each model will be trained to predict one specific month. I have tryed a lot and made some predictions on the training dataset and evaluated them on the test dataset, but I am still unsure about the windowing. Should it look like this to train my models right?
Last
consecutive Month in window
|
Sales
+ 1 horizon (label)
|
Sales-47
|
Sales-46
|
…
|
Sales-0
|
48
|
y49
|
Jan
2014
|
Feb
2014
|
…
|
Dec
2018
|
50
|
y50
|
Feb
2014
|
Mar
2014
|
…
|
Jan
2018
|
…
|
…
|
…
|
…
|
…
|
…
|
60
|
y59
|
Dez
2014
|
Jan
2015
|
…
|
Nov
2018 |
First row would be used to train and predict January 2018, secon to trainand predict Feb. 2018 and so on.
Thank you for any suggestion.