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imbalanced classification

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learning classifier from class-imbalanced data

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Leo-Q-316/ImGAGN

공식 코드

ImGAGN:Imbalanced Network Embedding via Generative Adversarial Graph Networks

https://github.com/Rattko/Bachelor-Thesis

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Benchmark of Data Preprocessing Methods for Imbalanced Classification

https://github.com/ReginaMayhem/ClusterBusters

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Meta-Learning for One-Class Classification with Few Examples using Order-Equivariant Network

https://github.com/Shounak-D/LexiBoost

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Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost Tuning

https://github.com/Varat7v2/adaptive-threshold

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Adaptive Threshold for Online Object Recognition and Re-identification Tasks

https://github.com/Xyc-arch/OPAL-OversamPling-with-Artificial-LLM-generated-data

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Synthetic Oversampling: Theory and A Practical Approach Using LLMs to Address Data Imbalance

https://github.com/ZhiningLiu1998/mesa

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MESA: Boost Ensemble Imbalanced Learning with MEta-SAmpler

https://github.com/ZhiningLiu1998/self-paced-ensemble

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Self-paced Ensemble for Highly Imbalanced Massive Data Classification

https://github.com/adrianstando/ecml-pkdd-2023-effects-of-data-balancing

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The Effect of Balancing Methods on Model Behavior in Imbalanced Classification Problems

https://github.com/adrianstando/edgaro

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The Effect of Balancing Methods on Model Behavior in Imbalanced Classification Problems

https://github.com/alinlab/M2m

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M2m: Imbalanced Classification via Major-to-minor Translation

https://github.com/amkatrutsa/edm

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Follow the bisector: a simple method for multi-objective optimization

https://github.com/angeloschatzimparmpas/hardvis

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HardVis: Visual Analytics to Handle Instance Hardness Using Undersampling and Oversampling Techniques

https://github.com/annie2603/ord

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Synthetic Tabular Data Generation for Imbalanced Classification: The Surprising Effectiveness of an Overlap Class

https://github.com/anonymous753341/ecgn

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ECGN: A Cluster-Aware Approach to Graph Neural Networks for Imbalanced Classification

https://github.com/baojianzhou/ftrl-auc

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Online AUC Optimization for Sparse High-Dimensional Datasets

https://github.com/baojianzhou/sparse-auc

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Stochastic Hard Thresholding Algorithms for AUC Maximization

https://github.com/caskcsg/spcl

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Supervised Prototypical Contrastive Learning for Emotion Recognition in Conversation

https://github.com/cl-tohoku/zipfian-whitening

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Zipfian Whitening

https://github.com/dream-lm/ingb_framework

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INGB: Informed Nonlinear Granular Ball Oversampling Framework for Noisy Imbalanced Classification

https://github.com/espectre/GCNs_on_imbalanced_datasets

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A Linkage-based Doubly Imbalanced Graph Learning Framework for Face Clustering

https://github.com/facebookresearch/feedback-guided-data-synthesis

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Feedback-guided Data Synthesis for Imbalanced Classification

https://github.com/fcjian/loce

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Exploring Classification Equilibrium in Long-Tailed Object Detection

https://github.com/frank-xwang/RIDE-LongTailRecognition

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Long-tailed Recognition by Routing Diverse Distribution-Aware Experts

https://github.com/frank-xwang/debiased-pseudo-labeling

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Debiased Learning from Naturally Imbalanced Pseudo-Labels

https://github.com/garcinc/noised-topk

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Stochastic smoothing of the top-K calibrated hinge loss for deep imbalanced classification

https://github.com/hankook/SLA

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Self-supervised Label Augmentation via Input Transformations

https://github.com/hhhhhhao/softmatch

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SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

https://github.com/ilyassmoummad/mix2

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Mixture of Mixups for Multi-label Classification of Rare Anuran Sounds

https://github.com/iosifidisvasileios/cumulativecostboosting

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AdaCC: Cumulative Cost-Sensitive Boosting for Imbalanced Classification

https://github.com/jhwjhw0123/Imbalance-XGBoost

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Imbalance-XGBoost: Leveraging Weighted and Focal Losses for Binary Label-Imbalanced Classification with XGBoost

https://github.com/jiawei-ren/BalancedMSE

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Balanced MSE for Imbalanced Visual Regression

https://github.com/jlyu55/imbalanced_classification

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A statistical theory of overfitting for imbalanced classification

https://github.com/jwwthu/MNIST-MIX

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MNIST-MIX: A Multi-language Handwritten Digit Recognition Dataset

https://github.com/jyansir/text2tree

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Text2Tree: Aligning Text Representation to the Label Tree Hierarchy for Imbalanced Medical Classification

https://github.com/klieberman/roc_lct

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Optimizing for ROC Curves on Class-Imbalanced Data by Training over a Family of Loss Functions

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