The appendix for the paper on Imbalanced Classification with Deep Reinforcement Learning: imbDRL.
NOTE: For cleaner examples of running your own experiments. See the imbDRL-repository. The sole purpose of this repository is to store the experiments used in the paper.
- Python 3.7+
- The required packages as listed in:
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 functionimbDRL.utils.split_csv
- This folder must contain
Install via pip
:
pip install imbDRL
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.