Open Mohamed209 opened 1 year ago
seems I found a workaround with using PAR models from deepecho as standalone library not from sdv
https://github.com/sdv-dev/DeepEcho#standalone-usage
So the question now , any intentions to support data_types
dict to be passed to PAR models from sdv ?
Hi @Mohamed209, glad you found that the DeepEcho
library had the settings you needed.
How about we turn this issue into a feature request for supporting all the PAR data_types
through the SDV library? While this is not currently on our roadmap, this type of feedback will help us prioritize it in the future.
(Following the previous comment, I've re-titled this and marked it as a feature request)
Environment details
Question description
I have a dataset where real features seems to follow NegativeBinomial distribution so per the paper
I want to force the loss during training for some features to use NegativeBinomial distribution
from
deepecho.py
all feature will be continuous , so while the training
all my features will be modeled as gaussian , which is not correct for my case