Tag: class imbalance

Researchers have developed CL3AN-GNN, a graph neural network that borrows curriculum learning from education to progressively disentangle features and boost ...

A new multi-stream deep learning framework called MS-AtroNet combines convolutional, state-space, wavelet, and evidential components to classify Alzheimer's MRI slices ...

Researchers have built an interpretable machine-learning framework that predicts sovereign default as a multi-class event, identifying which creditors a government ...

A benchmarking study in BMC Infectious Diseases shows that data balancing, feature selection, and hyperparameter tuning make machine learning models ...

A new study shows that lightweight transformer models can automatically classify the roles participants play in cyberbullying episodes, setting a ...

A rough set theory analysis of the METABRIC cohort shows that a compact set of routine clinical variables can moderately ...

A new multimodal AI framework called TriCCA-PPI fuses sequence, structure, and functional data through chained cross-attention to predict protein-protein interactions ...

Researchers have developed CALT-GNN, a graph neural network that combines cross-attention-based multi-omics integration with long-tail expert routing to improve cancer ...

Researchers have developed MLIDSC, a self-adaptive online active learning framework that maintains high accuracy on multiclass imbalanced data streams while ...

KAIST researchers combined physics-based preprocessing with a FiLM-conditioned convolutional neural network to classify weld defects in phased-array ultrasonic testing, reaching ...