How to treat missing continuous data in data set

[peter-jay-aut]

• CTGAN version:0.2.2
• Python version: 3.6.8
• Operating System: Tensorflow Docker

Description

Hi, I'm curious how to treat missing continuous values in a training Dataset. Using a placeholder that was used in the demo file ('?') for missing discrete values won't work. Any suggestions, how to deal with this issue?
Kind Regards!

[leix28]

Hi @peter-jay-aut

Current CTGAN does not support missing values. "?" is not the best way to handle missing values for discrete columns. "?" is treated as a normal category. I would suggest you to run missing value imputation before training CTGAN.

We may consider adding missing value imputation in the future.

[peter-jay-aut]

thank you very much for your reply!

[csala]

Closing this issue, as the question has already been responded.

Also adding that if you want to work with data that is not clean and completely ready for modeling, you might want to have a look at the sibling library SDV