Multi-target regression - one model or multiple submodels
krzjoa opened this issue · 1 comments
Hi,
I have a question regarding the multi-target regression tasks. I know how to do that with TFDF (passing a list of MultiTaskItem(label=target_column, task=tfdf.keras.Task.REGRESSION)
objects), but I'm curious, how it's implemented.
Does YDF create a separate submodel for each target variable or use one model to predict all the target variables simultaneously?
Hi,
This is a part of the library that's under active development, so the answer might change soon. The last release of TF-DF still has independent models for each objective. However, a recent commit to YDF allowed Multi-task learning where the output of models trained as secondary are used as input for the "primary" model. This (and possibly more) changes to Multi-task models will land withe next TF-DF version.