There are 4 repositories under class-imbalance topic.
Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切:论文、代码、框架与库
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
Class-imbalanced Ensemble Learning in Python. | 类别不平衡/长尾机器学习库
NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).
ICDE'20 | A general & effective ensemble framework for imbalanced classification. | 泛用,高效,鲁棒的类别不平衡学习框架
Parametric Contrastive Learning (ICCV2021) & GPaCo (TPAMI 2023)
Handle class imbalance intelligently by using variational auto-encoders to generate synthetic observations of your minority class.
NeurIPS’20 | Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题
Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
[ICML 2023] Change is Hard: A Closer Look at Subpopulation Shift
This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).
Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/
1st place of Kaggle's RSNA Screening Mammography Breast Cancer Detection competition
Machine learning model for Credit Card fraud detection
ResLT: Residual Learning for Long-tailed Recognition (TPAMI 2022)
Experiments to show the usage of deep learning to detect breast cancer from breast histopathology images
[ICLR 2023] Official Tensorflow implementation of "Distributionally Robust Post-hoc Classifiers under Prior Shifts"
Address imbalance classes in machine learning projects.
Multi-Disease Detection in Retinal Imaging based on Ensembling Heterogeneous Deep Learning Models
A Julia toolbox with resampling methods to correct for class imbalance.
R and Data Files from my YouTube Channel
Focal CTC for End-To-End OMR task with Class Imbalance, SangCTC (Part I)
(NeurIPS 2021) Realistic Evaluation of Transductive Few-Shot Learning
[MICCAI2019 & TMI2020] Overfitting under Class Imbalance: Anaylsis and Improvements for Medical Image Segmentation.
Build a CNN based model which can accurately detect melanoma
Machine Learning/Pattern Recognition Models to analyze and predict if a client will subscribe for a term deposit given his/her marketing campaign related data
Build a classification model for reducing the churn rate for a telecom company
[MICCAI2022] Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores.
ICSE'18: Tuning Smote
This project focuses on using the Semantic Segmentation Deep Learning architecture DeepLAbV3+ on the Agriculture-Vision dataset. We focus on improving the architecture's performance by solving the class imbalance problem present in the data.
DuBE: Duple-balanced Ensemble Learning from Skewed Data
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
Advanced Machine Learning Algorithms including Cost-Sensitive Learning, Class Imbalances, Multi-Label Data, Multi-Instance Learning, Active Learning, Multi-Relational Data Mining, Interpretability in Python using Scikit-Learn.
⛈️ Code for the paper "End-to-End Prediction of Lightning Events from Geostationary Satellite Images"