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A project to compare credit card fraud prediction between auto-encoder and some boosting, bagging models

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credit_fraud

A project to compare credit card fraud prediction between auto-encoder and some boosting, bagging models

The data is from kaggle.com

The mkdirs_ml.py file is used to generate the file structure. Use python mkdirs_ml.py to run it.

The analysis is run with the docker. To download the container, use docker pull jupyter/datascience-notebook.

To run the container, use docker run -it --rm -v "$PWD":/home/jovyan/work -p 8888:8888 jupyter/datascience-notebook.

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A project to compare credit card fraud prediction between auto-encoder and some boosting, bagging models

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