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Activity 5: Detecting Credit Card Fraud (python, sklearn)
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For this activity, I figured a lot of the data I have been messing around with wouldn't really work that well with Naive Bayes. But I ran into a dataset among the Kaggle datasets that looked perfect for Naive Bayes. It's a big file (with cleaned data) with anonymous data for 284,807 transactions. You can see my notebook here:

https://github.com/bradleyrobinson/Credi...ayes.ipynb 

I would love input, especially into how I can improve the accuracy (the ROC score is .89 for test data). Let me know!
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