imbalanced-classification

[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression

[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning

[NeurIPS'25]🛠️Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库

[NeurIPS 2020] Balanced Meta-Softmax for Long-Tailed Visual Recognition

[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond

Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.

LightGBM for handling label-imbalanced data with focal and weighted loss functions in binary and multiclass classification

Implementation code of RA-GCN: Graph Convolutional Network for Disease Prediction Problems with Imbalanced Data accepted by Medical Image Analysis Journal (MedIA 2022)

This is the official PyTorch implementation of the paper "Rethinking Re-Sampling in Imbalanced Semi-Supervised Learning" (Ju He, Adam Kortylewski, Shaokang Yang, Shuai Liu, Cheng Yang, Changhu Wang, Alan Yuille).

Code for ECML-PKDD 2022 paper "GraphMixup: Improving Class-Imbalanced Node Classification by Reinforcement Mixup and Self-supervised Context Prediction"

DGSSC: A Deep Generative Spectral-Spatial Classifier for Imbalanced Hyperspectral Imagery, TCSVT, 2022

(EMNLP 2023 Findings) Text2Tree: Aligning Text Representation to the Label Tree Hierarchy for Imbalanced Medical Classification.

Many algorithms for imbalanced data support binary and multiclass classification only. This approach is made for mulit-label classification (aka multi-target classification). 🌻

Predictors for Blood-Brain Barrier Permeability with resampling strategies based on B3DB database.

Pytorch implementation of Class Balanced Loss based on Effective number of Samples

RuleCOSI is a machine learning package that combine and simplifies tree ensembles and generates a single rule-based classifier that is smaller and simpler.

DuBE: Duple-balanced Ensemble Learning from Skewed Data

The official implementations of CIBM paper: Long-tailed Medical Diagnosis with Relation-aware Representation Learning and Iterative Classifier Calibration

The souce code of MICCAI'23 paper: Combat Long-tails in Medical Classification with Relation-aware Consistency and Virtual Features Compensation

This repository contains the source code for our MICCAI 2024 paper titled 'Active Label Refinement for Robust Training of Imbalanced Medical Image Classification Tasks in the Presence of High Label Noise.'