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imbDRLAppendix

The appendix for the paper on Imbalanced Classification with Deep Reinforcement Learning: imbDRL.

Requirements

  • Python 3.7+
  • pip install -r requirements.txt
  • Logs are by default saved in ./logs/
  • Trained models are by default saved in ./models/
  • Optional: ./data/ folder located at the root of this repository.
    • This folder must contain creditcard.csv downloaded from Kaggle if you would like to use the Credit Card Fraud dataset.
    • Note: creditcard.csv needs to be split in a seperate train and test file. Please use the function imbDRL.utils.split_csv

Running the experiments

  • For the creditcard-fraud dataset:
    • Run ./experiments/creditcardfraud/nn_dta.py to run experiments for the standard NN and the DTA-method.
    • Run ./experiments/creditcardfraud/dqn.py to run experiments for DQN-algorithm.

Data for the histology and AKI datasets are not publicly available. The code for the experiments can be found in the ./experiments/histology and ./experiments/aki folders.

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