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Please indicate the following details about the environment in which you found the bug:
CTGAN version: latest (June 7th, 2022)
Python version: 3.9.10
Operating System: windows (python venv)
Error Description
pandas performance warning
Steps to reproduce
I was simply running the model with arbitrary columns and the mimic-iv data.
no crash, multiple performance warnings, I believe it has something to do with the version of the pandas and not using the suggested pd.concat on the training process of the ctgan model
The text was updated successfully, but these errors were encountered:
Hi @oriel9p, nice to meet you. I can confirm that there are many warnings when fitting the model. Many are repeated. There seem to be only 2 unique sources that I'm pasting below:
/usr/local/lib/python3.7/dist-packages/sklearn/mixture/_base.py:282: ConvergenceWarning: Initialization 1 did not converge. Try different init parameters, or increase max_iter, tol or check for degenerate data.
ConvergenceWarning,
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
data[column_name] = data[column_name].to_numpy().flatten()
/usr/local/lib/python3.7/dist-packages/ctgan/data_transformer.py:111: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
For the first (ConvergenceWarning), we are using #202 to track the possibility of silencing these if they do not impact the end use.
For the second (SettingWithCopyWarning), the change may require some more investigation. You can follow along in #215.
Since we have existing issues for these warnings, I'll close this issue off as a duplicate. If there is other output you are observing, feel free to reply and I'll reopen this issue.
Environment Details
Please indicate the following details about the environment in which you found the bug:
Error Description
pandas performance warning
Steps to reproduce
I was simply running the model with arbitrary columns and the mimic-iv data.
The text was updated successfully, but these errors were encountered: