Cover Image

Correcting Performance Estimation Bias in Imbalanced Classification with Minority Subconcepts

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Maxson, Taylor, Corizzo, Roberto, Wu, Yaning, Japkowicz, Nathalie, Bellinger, Colin
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights
by: Faber, Kamil, et al.
Published: (2023)

E-CaTCH: Event-Centric Cross-Modal Attention with Temporal Consistency and Class-Imbalance Handling for Misinformation Detection
by: Mousavi, Ahmad, et al.
Published: (2025)

Using LLMs to discover emerging coded antisemitic hate-speech in extremist social media
by: Kikkisetti, Dhanush, et al.
Published: (2024)

xLSTMAD: A Powerful xLSTM-based Method for Anomaly Detection
by: Faber, Kamil, et al.
Published: (2025)

TinySubNets: An efficient and low capacity continual learning strategy
by: Pietroń, Marcin, et al.
Published: (2024)

Towards efficient deep autoencoders for multivariate time series anomaly detection
by: Pietroń, Marcin, et al.
Published: (2024)

Monitoring the evolution of antisemitic discourse on extremist social media using BERT
by: Mustafa, Raza Ul, et al.
Published: (2024)

TSN-Affinity: Similarity-Driven Parameter Reuse for Continual Offline Reinforcement Learning
by: Żurek, Dominik, et al.
Published: (2026)

Large Language Models for Imbalanced Classification: Diversity makes the difference
by: Nguyen, Dang, et al.
Published: (2025)

SMOGAN: Synthetic Minority Oversampling with GAN Refinement for Imbalanced Regression
by: Alahyari, Shayan, et al.
Published: (2025)

Pure Node Selection for Imbalanced Graph Node Classification
by: Zeng, Fanlong, et al.
Published: (2025)

AD-NEv++ : The multi-architecture neuroevolution-based multivariate anomaly detection framework
by: Pietroń, Marcin, et al.
Published: (2024)

Mitigating Participation Imbalance Bias in Asynchronous Federated Learning
by: Chang, Xiangyu, et al.
Published: (2025)

Dynamic Observation Policies in Observation Cost-Sensitive Reinforcement Learning
by: Bellinger, Colin, et al.
Published: (2023)

Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection
by: Liu, Huafeng, et al.
Published: (2024)

ART: Adaptive Resampling-based Training for Imbalanced Classification
by: Basandrai, Arjun, et al.
Published: (2025)

Rethinking the Harmonic Loss via Non-Euclidean Distance Layers
by: Miller-Golub, Maxwell, et al.
Published: (2026)

AxelSMOTE: An Agent-Based Oversampling Algorithm for Imbalanced Classification
by: Kishanthan, Sukumar, et al.
Published: (2025)

VIGraph: Generative Self-supervised Learning for Class-Imbalanced Node Classification
by: Hu, Yulan, et al.
Published: (2023)

Evaluating Anomaly Detectors for Simulated Highly Imbalanced Industrial Classification Problems
by: Wheat, Lesley, et al.
Published: (2025)

HyperSMOTE: A Hypergraph-based Oversampling Approach for Imbalanced Node Classifications
by: Zhao, Ziming, et al.
Published: (2024)

GraphIFE: Rethinking Graph Imbalance Node Classification via Invariant Learning
by: Zeng, Fanlong, et al.
Published: (2025)

BuffGraph: Enhancing Class-Imbalanced Node Classification via Buffer Nodes
by: Wang, Qian, et al.
Published: (2024)

Lost or Hidden? A Concept-Level Forgetting in Supervised Continual Learning
by: Filus, Katarzyna, et al.
Published: (2026)

Minor First, Major Last: A Depth-Induced Implicit Bias of Sharpness-Aware Minimization
by: Moon, Chaewon, et al.
Published: (2026)

Transparency and Proportionality in Post-Processing Algorithmic Bias Correction
by: Ferreira, Juliett Suárez, et al.
Published: (2025)

SamGoG: A Sampling-Based Graph-of-Graphs Framework for Imbalanced Graph Classification
by: Wang, Shangyou, et al.
Published: (2025)

Learning to Estimate Package Delivery Time in Mixed Imbalanced Delivery and Pickup Logistics Services
by: Yi, Jinhui, et al.
Published: (2025)

Rethinking Refinement: Correcting Generative Bias without Noise Injection
by: Peng, Xin, et al.
Published: (2026)

EMA Without the Lag: Bias-Corrected Iterate Averaging Schemes
by: Block, Adam, et al.
Published: (2025)

The Geometry of Harmfulness in LLMs through Subconcept Probing
by: Shah, McNair, et al.
Published: (2025)

A Direct Classification Approach for Reliable Wind Ramp Event Forecasting under Severe Class Imbalance
by: Morales-Hernández, Alejandro, et al.
Published: (2026)

Enhancing Imbalanced Node Classification via Curriculum-Guided Feature Learning and Three-Stage Attention Network
by: Fofanah, Abdul Joseph, et al.
Published: (2026)

Imbalance in Regression Datasets
by: Kowatsch, Daniel, et al.
Published: (2024)

Graph Negative Feedback Bias Correction Framework for Adaptive Heterophily Modeling
by: Lv, Jiaqi, et al.
Published: (2026)

CoRPO: Adding a Correctness Bias to GRPO Improves Generalization
by: Garg, Anisha, et al.
Published: (2025)

EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models
by: Kim, Jinhee, et al.
Published: (2024)

NodeReg: Mitigating the Imbalance and Distribution Shift Effects in Semi-Supervised Node Classification via Norm Consistency
by: Yang, Shenzhi, et al.
Published: (2025)

On Imbalanced Regression with Hoeffding Trees
by: Alchirch, Pantia-Marina, et al.
Published: (2026)

PIMPC-GNN: Physics-Informed Multi-Phase Consensus Learning for Enhancing Imbalanced Node Classification in Graph Neural Networks
by: Fofanah, Abdul Joseph, et al.
Published: (2026)