imbalanced-learning
There are 213 repositories under imbalanced-learning topic.
ZhaoJ9014/face.evoLVe
🔥🔥High-Performance Face Recognition Library on PaddlePaddle & PyTorch🔥🔥
ZhiningLiu1998/awesome-imbalanced-learning
😎 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
YyzHarry/imbalanced-regression
[ICML 2021, Long Talk] Delving into Deep Imbalanced Regression
YyzHarry/imbalanced-semi-self
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
analyticalmindsltd/smote_variants
A collection of 85 minority oversampling techniques (SMOTE) for imbalanced learning with multi-class oversampling and model selection features
zzw-zwzhang/Awesome-of-Long-Tailed-Recognition
A curated list of long-tailed recognition resources.
jiawei-ren/BalancedMSE
[CVPR 2022 Oral] Balanced MSE for Imbalanced Visual Regression https://arxiv.org/abs/2203.16427
ZhiningLiu1998/imbalanced-ensemble
🛠️ Class-imbalanced Ensemble Learning Toolbox. | 类别不平衡/长尾机器学习库
kochlisGit/ProphitBet-Soccer-Bets-Predictor
ProphitBet is a Machine Learning Soccer Bet prediction application. It analyzes the form of teams, computes match statistics and predicts the outcomes of a match using Advanced Machine Learning (ML) methods. The supported algorithms in this application are Neural Networks, Random Forests & Ensembl Models.
ZhiningLiu1998/self-paced-ensemble
[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
dvlab-research/Parametric-Contrastive-Learning
Parametric Contrastive Learning (ICCV2021) & GPaCo (TPAMI 2023)
prstrive/UniMVSNet
[CVPR 2022] Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation
solegalli/machine-learning-imbalanced-data
Code repository for the online course Machine Learning with Imbalanced Data
jiawei-ren/BalancedMetaSoftmax-Classification
[NeurIPS 2020] Balanced Meta-Softmax for Long-Tailed Visual Recognition
YyzHarry/multi-domain-imbalance
[ECCV 2022] Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization, and Beyond
ZhiningLiu1998/mesa
[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
Albertsr/Class-Imbalance
Cost-Sensitive Learning / ReSampling / Weighting / Thresholding / BorderlineSMOTE / AdaCost / etc.
MaxHalford/pytorch-resample
🎲 Iterable dataset resampling in PyTorch
GZWQ/Awesome-Long-Tailed
Papers about long-tailed tasks
yanliang3612/awesome-imbalanced-learning-on-graphs
A repository contains a collection of resources and papers on Imbalance Learning On Graphs
he-zh/vibration_gan
Implement GANs to generate time-series signals for imbalanced learning problem. The experiments are conducted using CWRU bearing data.
Xtra-Computing/Awesome-Literature-ILoGs
Awesome literature on imbalanced learning on graphs
jiequancui/ResLT
ResLT: Residual Learning for Long-tailed Recognition (TPAMI 2022)
massquantity/Class-Imbalance
《机器学习之类别不平衡问题》文章代码
BorealisAI/ranksim-imbalanced-regression
[ICML 2022] RankSim: Ranking Similarity Regularization for Deep Imbalanced Regression
Treers/MetaCost
P. Domingos proposed a principled method for making an arbitrary classifier cost-sensitive by wrapping a cost-minimizing procedure around it. The procedure, called MetaCost, treats the underlying classifier as a black box, requiring no knowledge of its functioning or change to it.
NeuralCollapseApplications/ImbalancedLearning
[NeurIPS 2022] The official code for our NeurIPS 2022 paper "Inducing Neural Collapse in Imbalanced Learning: Do We Really Need a Learnable Classifier at the End of Deep Neural Network?".
lancopku/well-classified-examples-are-underestimated
Code for the AAAI 2022 publication "Well-classified Examples are Underestimated in Classification with Deep Neural Networks"
georgedouzas/geometric-smote
Implementation of the Geometric SMOTE over-sampling algorithm.
jinyan-06/SHIKE
Long-Tailed Visual Recognition via Self-Heterogeneous Integration with Knowledge Excavation (CVPR 2023)
iamyuanchung/csdnn
Theano implementation of Cost-Sensitive Deep Neural Networks
paobranco/SMOGN-LIDTA17
SMOGN: a Pre-processing Approach for Imbalanced Regression - LIDTA2017
ricardoamferreira/Predicting-Adverse-Drug-Reactions-with-Machine-Learning
The objective of this work is to develop machine learning (ML) methods that can accurately predict adverse drug reactions (ADRs) using the databases SIDER and OFFSIDES.
farhantandia/Tricks-for-Handling-Imbalanced-Dataset-Image-Classification
Some trick for handling imbalanced dataset
mjuez/approx-smote
Approx-SMOTE: fast SMOTE for Big Data on Apache Spark
nunompmoniz/IRon
R Package for Imbalanced Regression