Hi Everyone, Can Someone guide me how to use Xgboost regression for time series data?
The general sentiment is that XGBoost isn't meant for time series applications. It can be done, but would require transformation/modification of the input data and procedures.Is there a reason why you're looking to boosted models instead of the time series tools available in Alteryx?
Hi @CharlieS Reason behind using Boosting model is Time series tools in Alteryx is not customizable for the data i have.
workflow0's
You can download TS Model Factory tool to answer your question, it does a group by TS model.
I assume in practice you will use all three years of data to feed the model rather than using average, otherwise you won't have enough rows, so I created some dummy values to pad out the data you supplied.
Though I would be much more concerned about the 0 in the data, they would significantly impact your model. If there is only a few rows missing, you can estimate them, but there are too many dates missing, then you need find additional data or may need to drop some ID.
Hi @leozhang2work Thanks for the workflow. I've gone through it and found that the forecast is having a constant value for most of the IDs throughout the year. Why is it like that?
@Ivaturi_Vighnesh wrote: Hi @leozhang2work Thanks for the workflow. I've gone through it and found that the forecast is having a constant value for most of the IDs throughout the year. Why is it like that?
The default settings of the ARIMA tools is to use the most recent value as the forecast the future values (which is called the naïve method). Now that the tool is working, it is up to the user to configure the model for the particular scenario based on the available data and desired hypothesis testing. The model customization settings allow the user to adjust parameters like differencing, seasonality, drift, and many more.
Here's a link to the suggested handbook for time series modeling:
https://otexts.com/fpp2/
