Classification on Simulated high-dimensional dataset nine simulation scenarios (test)

92.6AccuracyengGNN

Evaluation results

Method
engGNN2026.01	92.6	0.98	90.6
GEDFNe2026.01	92.4	0.98	90.3
engGNN2026.01	92.3	0.981	90.3
GEDFNxgb2026.01	92.3	0.981	90.2
GEDFNrf2026.01	92.1	0.978	90.4
GEDFNrf2026.01	92	0.978	89.7
GEDFNxgb2026.01	92	0.978	89.8
GEDFNxgb2026.01	91.9	0.976	89.4
GEDFNrf2026.01	91.4	0.976	88.6
GEDFNe2026.01	91.4	0.975	89
GEDFNe2026.01	91.3	0.972	88.9
DFN2026.01	91.3	0.974	88.8
engGNN2026.01	91.2	0.968	88.5
GEDFNxgb2026.01	91	0.972	88.6
GEDFNxgb2026.01	91	0.975	88.2
engGNN2026.01	90.9	0.972	88.4
engGNN2026.01	90.8	0.972	88.5
engGNN2026.01	90.8	0.971	87.9
GEDFNrf2026.01	90.8	0.968	88.2
GEDFNe2026.01	90.6	0.963	88.3
GEDFNxgb2026.01	90.6	0.971	88
engGNN2026.01	90.5	0.974	88.1
XGBoost2026.01	90.5	0.969	88
DFN2026.01	90.5	0.97	87.9
GEDFNe2026.01	90.5	0.97	87.8
GEDFNrf2026.01	90.4	0.971	87.8
GEDFNrf2026.01	90.3	0.965	87.5
GEDFNxgb2026.01	90.2	0.963	87.7
GEDFNe2026.01	90	0.969	87.8
XGBoost2026.01	89.8	0.963	86.7
XGBoost2026.01	89.6	0.964	86.6
DFN2026.01	89.3	0.961	86.5
DFN2026.01	89.2	0.963	87
GEDFNe2026.01	88.9	0.965	85.7
GEDFNe2026.01	88.6	0.951	84.7
GEDFNrf2026.01	88.6	0.959	84.1
XGBoost2026.01	88.3	0.959	84.7
DFN2026.01	88.2	0.954	84.7
DFN2026.01	88	0.955	85.3
GEDFNrf2026.01	87.7	0.956	83.6
XGBoost2026.01	87.4	0.944	83.4
engGNN2026.01	87	0.946	83.8
RF2026.01	87	0.94	83
engGNN2026.01	86.8	0.952	83.3
GEDFNrf2026.01	86.8	0.949	83.1
RF2026.01	86.6	0.942	82.6
DFN2026.01	86.5	0.943	83
XGBoost2026.01	86.4	0.947	81.8
DFN2026.01	86.1	0.932	82.7
GEDFNxgb2026.01	86	0.955	83.4
GEDFNxgb2026.01	85.9	0.952	81.8
XGBoost2026.01	85.9	0.947	82.4
RF2026.01	85.8	0.944	81.2
RF2026.01	85.8	0.942	81.7
XGBoost2026.01	85.6	0.935	81.1
RF2026.01	85.1	0.927	80.2
GEDFNe2026.01	84.8	0.943	80.1
RF2026.01	84.8	0.927	80.7
RF2026.01	84.5	0.93	79.6
DFN2026.01	83.9	0.937	79.7
RF2026.01	83.4	0.926	77.3
XGBoost2026.01	83.3	0.921	78.4
RF2026.01	81.8	0.909	76.2