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ResearchFormerly WizWand

Classification on car

99.9AccuracyCatBoost
23.04442.99762.9582.903Mar 18, 2025May 24, 2025Jul 31, 2025Oct 7, 2025Dec 13, 2025Feb 19, 2026Apr 28, 2026
Updated 5mo ago

Evaluation results

MethodLinks
CatBoostPredictor=CatBoost, Feature Engineering=Base2025.0399.9——
CatBoostPredictor=CatBoost, Feature Engineering=LLM-FE2025.0399.9——
XGBoostPredictor=XGBoost, Feature Engineering=LLM-FE2025.0399.9——
CAAFEBackbone=XGBoost, n (number of samples)=1728, p (number of features)=62025.0399.9——
LLM-FEBackbone=XGBoost, n (number of samples)=1728, p (number of features)=62025.0399.9——
AutoFeatBackbone=XGBoost, n (number of samples)=1728, p (number of features)=62025.0399.8——
OpenFEBackbone=XGBoost, n (number of samples)=1728, p (number of features)=62025.0399.8——
TabPFNPredictor=TabPFN, Feature Engineering=LLM-FE2025.0399.6——
XGBoostPredictor=XGBoost, Feature Engineering=Base2025.0399.5——
BaseBackbone=XGBoost, n (number of samples)=1728, p (number of features)=62025.0399.5——
OCTreeBackbone=XGBoost, n (number of samples)=1728, p (number of features)=62025.0399.5——
UncalibratedBase Model=MLP2026.0399.1——
MSBase Model=MLP2026.0399.1——
OIBase Model=MLP2026.0399.1——
TSBase Model=MLP2026.0399.1——
BinBase Model=MLP2026.0398.8——
DirBase Model=MLP2026.0398.8——
BrenierIRBase Model=MLP, k=302026.0398.8——
BrenierIRBase Model=MLP, k=502026.0398.8——
IRPBase Model=MLP2026.0398.6——
IRBase Model=MLP2026.0398.6——
TabPFNPredictor=TabPFN, Feature Engineering=Base2025.0398.4——
BrenierIRBase Model=MLP, k=152026.0396.5——
MLPPredictor=MLP, Feature Engineering=LLM-FE2025.0395——
MLPPredictor=MLP, Feature Engineering=Base2025.0392.9——
IRBase Model=linear SVM2026.0390.8——
BinBase Model=linear SVM2026.0389.3——
UncalibratedBase Model=linear SVM2026.0388.2——
IRPBase Model=linear SVM2026.0388.2——
BrenierIRBase Model=linear SVM, k=302026.0388.1——
BrenierIRBase Model=linear SVM, k=502026.0387.9——
BrenierIRBase Model=linear SVM, k=152026.0386——
SVM2026.0481.70.338—
FeatLLMBackbone=XGBoost, n (number of samples)=1728, p (number of features)=62025.0380.8——
DFSOS-12026.04771.01879.3
DFSOS-22026.04770.93779.3
ADMM2026.0476.50.4861.2
MSBase Model=linear SVM2026.0375.4——
APG2026.04750.97197.7
DirBase Model=linear SVM2026.0373.7——
1-NN2026.0471.70.025—
Logistic RegressionPredictor=Logistic Regression, Feature Engineering=LLM-FE2025.0369.6——
Logistic RegressionPredictor=Logistic Regression, Feature Engineering=Base2025.0369——
10-NN2026.04600.016—
5-NN2026.0458.30.023—
OIBase Model=linear SVM2026.0326——
TSBase Model=linear SVM2026.0326——