[MXNet Forum] [Gluon] How to supply custom loss function to autogluon to minimise?

[barmanroys via MXNet Forum <mx...@discoursemail.com.INVALID>]

Using Autogluon for supervised regression problem. I wonder how to use Mean Absolute Percentage Error (MAPE) as a loss function and better still, supply a custom loss function to autogluon? This is how my versions look like. 


```
autogluon==0.2.0
autogluon-contrib-nlp==0.0.1b20210201
autogluon.core==0.2.0
autogluon.extra==0.2.0
autogluon.features==0.2.0
autogluon.mxnet==0.2.0
autogluon.tabular==0.2.0
autogluon.text==0.2.0
autogluon.vision==0.2.0
gluoncv==0.10.3.post0
gluonts==0.7.3
mxnet==1.8.0.post0
```
I am supplying ```eval_metric='mean_absolute_error'``` in the ```TabularPredictor``` constructor, but is it actually the loss function that the engine is minimising or is it just for reporting purpose? I do not see any loss parameter like I usually supply in Tensorflow, so any documentation around how the signature of a custom loss function would look like and where to supply it would be great.





---
[Visit Topic](https://discuss.mxnet.apache.org/t/how-to-supply-custom-loss-function-to-autogluon-to-minimise/7014/1) or reply to this email to respond.

You are receiving this because you enabled mailing list mode.

To unsubscribe from these emails, [click here](https://discuss.mxnet.apache.org/email/unsubscribe/02115e384f2939a2c252872b7f9bdcbcff8a17d3c6c1fc3765453f0dff5361cc).