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Classification on Wine (test)

100AccuracySklearn
75.601681.935888.2794.6042Jun 9, 2021Apr 12, 2022Feb 14, 2023Dec 19, 2023Oct 22, 2024Aug 26, 2025Jun 30, 2026
Updated 4mo ago

Evaluation results

MethodLinks
SklearnModel architecture=Linear model, Loss function=Logistic regression, Solver=L-BFGS2022.05100——
Cross-entropyModel architecture=Linear model, Loss function=Cross-entropy2022.05100——
HingeModel architecture=Linear model, Loss function=Hinge2022.05100——
EXACTModel architecture=Linear model, Loss function=EXACT2022.05100——
LDAType=Euclidean, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.02100——
R-PGAType=Riemannian, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.02100——
R-RPCAType=Riemannian, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.02100——
R-LDAType=Riemannian, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.02100——
R-IsomapType=Riemannian, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.02100——
KANSample size=178, Validation protocol=5-fold cross-validation2026.0598.3——
PCAType=Euclidean, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.0298.2——
R-LEType=Riemannian, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.0298.2——
ReMLPSelection Category=Dynamic, Optimization Strategy=RL2025.0898.15——
MLPSelection Category=Dynamic, Optimization Strategy=RL2025.0897.84——
Soft LearningSample size=178, Validation protocol=5-fold cross-validation2026.0597.8——
RFSample size=178, Validation protocol=5-fold cross-validation2026.0597.7——
XBNet2021.0697.22——
XGBoost2021.0697.22——
CatBoostSample size=178, Validation protocol=5-fold cross-validation2026.0597.2——
IsomapType=Euclidean, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.0296.3——
VIPSelection Category=Dynamic, Optimization Strategy=Greedy2025.0896.29——
GBTSample size=178, Validation protocol=5-fold cross-validation2026.0596.1——
Static CMISelection Category=Static2025.0895.37——
R-ONPPType=Riemannian, Number of components (nc)=3, Subsampling strategy=stratified, max 2000 samples2026.0294.4——
CARTSelection Category=Dynamic, Optimization Strategy=Greedy2025.0892.28——
Tuned MLPSample size=178, Validation protocol=5-fold cross-validation2026.0592.1——
CARTSelection Category=Dynamic, Optimization Strategy=RL2025.0891.36——
FtreeSelection Category=Dynamic, Optimization Strategy=RL2025.0890.74——
XGBoost2026.0688.64——
XGBoostDeferral rate=0%2026.0688.64—0.0022
Random Forest2026.0688.48——
Random ForestDeferral rate=0%2026.0688.48—0.0042
MDT+XGBmax_test_deferral_rate=25%2026.0687.88——
MDT+XGBDeferral rate=≤25%2026.0687.88—0.0052
FTreeSelection Category=Dynamic, Optimization Strategy=Greedy2025.0887.34——
TabNetSelection Category=Static2025.0886.73——
ReMLPSelection Category=Dynamic, Optimization Strategy=Greedy2025.0884.57——
FIGS2026.0683.91——
FIGSDeferral rate=0%2026.0683.91—0.0039
Non-Deferral Tree2026.0683.4——
Non-Deferral TreeDeferral rate=0%2026.0683.4—0.0015
CWCFSelection Category=Dynamic, Optimization Strategy=RL2025.0883.33——
DIMESelection Category=Dynamic, Optimization Strategy=Greedy2025.0879.01——
INVASESelection Category=Dynamic, Optimization Strategy=Greedy2025.0878.71——
MLPSelection Category=Dynamic, Optimization Strategy=Greedy2025.0876.54——
ArrowFlowN=178, Feat=13, Cls=3, ArrowFlow Config=[128] e=64 p=12026.04—2.8—
DTE-1variant=DTE-12025.12—8.2—
DTE-3variant=DTE-32025.12—2.4—
Forest2025.12—2—
KNNN=178, Feat=13, Cls=32026.04—0—
MLPN=178, Feat=13, Cls=32026.04—2.8—
RFN=178, Feat=13, Cls=32026.04—0—
S-NN2025.12—2.4—
SVMN=178, Feat=13, Cls=32026.04—2.8—
Tree2025.12—10.3—
XGBN=178, Feat=13, Cls=32026.04—2.8—