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I ran a batch of new simulations, and I'm finding that in every case of fraud, the newbalanceOrig is =0. When comparing this to non-fraudulent transactions
I didn't have this problem when modeling the original data set on kaggle from 2017.
Essentially this is causing models to "overfit". I can upload files ect if you're curious. If this is an issue on my end with improperly setting parameters when synthetically creating the data I'd also like to know. In my case I used the default params.
The text was updated successfully, but these errors were encountered:
I ran a batch of new simulations, and I'm finding that in every case of fraud, the newbalanceOrig is =0. When comparing this to non-fraudulent transactions
I didn't have this problem when modeling the original data set on kaggle from 2017.
Essentially this is causing models to "overfit". I can upload files ect if you're curious. If this is an issue on my end with improperly setting parameters when synthetically creating the data I'd also like to know. In my case I used the default params.
The text was updated successfully, but these errors were encountered: