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imbalanced classification

learning classifier from class-imbalanced data

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Showing 151–200 of 211 papers

TitleStatusHype
GMOTE: Gaussian based minority oversampling technique for imbalanced classification adapting tail probability of outliers—0
A Minimax Probability Machine for Non-Decomposable Performance Measures—0
Provably Training Overparameterized Neural Network Classifiers with Non-convex Constraints—0
ReMix: Calibrated Resampling for Class Imbalance in Deep learning—0
Binary Classification: Counterbalancing Class Imbalance by Applying Regression Models in Combination with One-Sided Label Shifts—0
Improving Model Accuracy for Imbalanced Image Classification Tasks by Adding a Final Batch Normalization Layer: An Empirical Study—0
Stochastic Hard Thresholding Algorithms for AUC MaximizationCode0
Nonlinear Monte Carlo Method for Imbalanced Data Learning—0
Oversampling Tabular Data with Deep Generative Models: Is it worth the effort?—0
Weakly Supervised-Based Oversampling for High Imbalance and High Dimensionality Data Classification—0
Online AUC Optimization for Sparse High-Dimensional DatasetsCode0
Variational Disentanglement for Rare Event ModelingCode0
Towards Stable Imbalanced Data Classification via Virtual Big Data Projection—0
Counterfactual-based minority oversampling for imbalanced classification—0
Follow the bisector: a simple method for multi-objective optimizationCode0
Meta-Learning for One-Class Classification with Few Examples using Order-Equivariant NetworkCode0
Hashing-Based Undersampling Ensemble for Imbalanced Pattern Classification ProblemsCode0
Class-Weighted Classification: Trade-offs and Robust ApproachesCode0
Minority Class Oversampling for Tabular Data with Deep Generative Models—0
MNIST-MIX: A Multi-language Handwritten Digit Recognition DatasetCode0
Deep Synthetic Minority Over-Sampling Technique—0
CNN-based Repetitive self-revised learning for photos' aesthetics imbalanced classification—0
Imbalanced classification: a paradigm-based review—0
Infrequent adverse event prediction in low carbon energy production using machine learning—0
Smart Data driven Decision Trees Ensemble Methodology for Imbalanced Big Data—0
A Self-Adaptive Synthetic Over-Sampling Technique for Imbalanced Classification—0
Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data—0
Self-supervised Label Augmentation via Input TransformationsCode0
Generative Adversarial Networks for Failure Prediction—0
Revisiting Classical Bagging with Modern Transfer Learning for On-the-fly Disaster Damage Detector—0
Imbalance-XGBoost: Leveraging Weighted and Focal Losses for Binary Label-Imbalanced Classification with XGBoostCode0
Stochastic Proximal AUC Maximization—0
CRCEN: A Generalized Cost-sensitive Neural Network Approach for Imbalanced Classification—0
Personalized Colorectal Cancer Survivability Prediction with Machine Learning Methods—0
Prototypical Metric Transfer Learning for Continuous Speech Keyword Spotting With Limited Training Data—0
Deep Reinforcement Learning for Imbalanced ClassificationCode0
Adversarial Classifier for Imbalanced Problems—0
Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning—0
Superensemble Classifier for Improving Predictions in Imbalanced Datasets—0
Deep Learning using K-space Based Data Augmentation for Automated Cardiac MR Motion Artefact Detection—0
Robust Tracking via Weighted Online Extreme Learning Machine—0
Instance-based entropy fuzzy support vector machine for imbalanced data—0
Stochastic Proximal Algorithms for AUC Maximization—0
A Cost-Sensitive Deep Belief Network for Imbalanced Classification—0
CUSBoost: Cluster-based Under-sampling with Boosting for Imbalanced ClassificationCode0
Boosting with Lexicographic Programming: Addressing Class Imbalance without Cost TuningCode0
QUB at SemEval-2017 Task 6: Cascaded Imbalanced Classification for Humor Analysis in Twitter—0
Influence of Resampling on Accuracy of Imbalanced Classification—0
The Prediction Advantage: A Universally Meaningful Performance Measure for Classification and Regression—0
Semi-Supervised AUC Optimization based on Positive-Unlabeled Learning—0
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