Tag: SMOTE

An international research team has built an open, reproducible machine learning workflow that classifies honey seasons as poor, moderate, or ...

A leakage-free benchmark of ten chronic-disease cohorts finds that no outlier-removal method beats doing nothing, while data-cleaning steps silently delete ...

A multimodal deep learning model combining histopathological images with clinical data achieved 97.17 percent accuracy in stratifying colorectal cancer patients ...

Researchers have developed a two-level evaluation framework showing that synthetic vertebrae which score highly on geometric similarity can still fail ...

Researchers have built a nomogram that fuses spectral CT imaging data with clinical blood markers to predict how aggressively colorectal ...

Researchers have developed a geometry-aware oversampling method that uses neural density fields and meta-learning to generate synthetic minority-class samples adapted ...

A self-training LightGBM framework developed at Jilin University recognizes mineralization-related geochemical anomalies in Inner Mongolia using sparse labeled and vast ...

Researchers at Yantai University have developed SSAO, an adaptive oversampling method that uses Gaussian mixture model clustering and minimum enclosing ...

Researchers have developed a noise-robust over-sampling method called mZ-cEAMD that outperforms SMOTE-based techniques in classifying defective car transmissions from severely ...