This repository is the official PyTorch implementation of Meta-Balance. Find the paper on arxiv
MetaBalance: High-Performance Neural Networks for Class-Imbalanced Data
MetaCifar
Cifar10 dataset is downloaded by the code itself. Both the Severe and Moderate Class Imbalance is simulated by the code as well.
cd MetaCifar
Severely Imbalanced Cifar10 data
python3 train.py
--dataset_create
--dataset_type 'severe_imbalance'
--comet_key 'key'
Moderately Imbalanced Cifar10 data
python3 train.py
--dataset_create
--dataset_type 'imbalance'
--comet_key 'key'
MetaFace
Need to download the CelebA dataset from this link. The Training and Testing splits are further explained in the paper.
cd MetaFace
python3 train.py
--modify_data
--modify_gender 'women'
--proportion 0.1
--data_train_root '/loc/to/training/data'
--data_test_root '/loc/to/testing/data'
--comet_key 'key'
MetaCC
Download the Loan Default datset from this link inside MetaCC.
cd MetaCC
python3 Meta_credit_card_fraud.py
MetaLD
Download the Loan Default datset from this link inside MetaLD.
cd MetaLD
python3 Meta_loan_default.py