04:00
2026-10-07
machinebrief.com
machine-learning
Neutrosophic Ensemble Classification for Uncertainty-Aware Bearing Fault Detection: Evidence from Laboratory and Variable-Speed Industrial Benchmarks
A neutrosophic ensemble of Random Forest, XGBoost and Logistic Regression reached 100.00 percent accuracy on three of four held-out CWRU bearing-fault loads (92.27 percent on the fourth) but collapsed…