There are 5 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 Toolbox. | 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, efficient 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
Machine learning model for Credit Card fraud detection
This is the code for Addressing Class Imbalance in Federated Learning (AAAI-2021).
1st place solution of RSNA Screening Mammography Breast Cancer Detection competition on Kaggle: https://www.kaggle.com/competitions/rsna-breast-cancer-detection
Python package for tackling multi-class imbalance problems. http://www.cs.put.poznan.pl/mlango/publications/multiimbalance/
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
(NeurIPS 2021) Realistic Evaluation of Transductive Few-Shot Learning
Focal CTC for End-To-End OMR task with Class Imbalance, SangCTC (Part I)
Build a CNN based model which can accurately detect melanoma
[MICCAI2019 & TMI2020] Overfitting under Class Imbalance: Anaylsis and Improvements for Medical Image Segmentation.
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
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
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.
[MICCAI2022] Estimating Model Performance under Domain Shifts with Class-Specific Confidence Scores.
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.
DuBE: Duple-balanced Ensemble Learning from Skewed Data
The Python Class Overlap Libray (pycol) assembles a comprehensive set of complexity measures associated with the characterization of the Class Overlap problem.