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I also want to know, if I just: pip install ctgan, and then write a piece of code to use CTGAN to generate synthetic data for my dataset, how can I evaluate whether the generated data is good or bad
BTW -- while you are welcome to try using CTGAN as a standalone library, we actually recommend using it via the SDV library instead. Within SDV, the CTGANSynthesizer is a wrapper around this one, but it allows additional features such as data pre-processing, as well as more convenient visualizations, metrics, etc.
What metrics could we apply to measure the likelihood of the generated data regarding the real data?
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