is there a difference between using one model per target value vs using one model for all targets with loss function set as multiRMSE ? Or will both methods give the same predictive power for each target value?
How does one implement multiple regression in catboost?
With setting the loss function to MultiRmse or MultiRmsewithmissingvalues
https://catboost.ai/en/docs/concepts/loss-functions-multiregression#MultiRMSE Yip, just set loss function = "MultiRMSE" when you define your model.
I just saw people on forums complaining on how this link barely explains anything, I only found an old kaggle notebook for sample catboost multi regression code. So a friendly advice for you guys would be adding a basic sample code here. I think this is a huge feature and would put you ahead of many algorithms if people knew this existed.
IT especially leacks the mention that it also works with missing values in the target variables, which makes it pretty unique
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