You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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?
The text was updated successfully, but these errors were encountered:
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.
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?
The text was updated successfully, but these errors were encountered: