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ResearchFormerly WizWand

Classification on credit-g

0.8ROC AUCCatBoost
0.475520.559760.6440.72824Feb 19, 2026Mar 12, 2026Apr 3, 2026Apr 25, 2026May 16, 2026Jun 7, 2026Jun 29, 2026
Updated 3mo ago

Evaluation results

MethodLinks
CatBoost2026.060.8—
RF2026.060.794—
IMN2026.060.794—
LR2026.060.784—
LFR-IMN2026.060.784—
CAAFEfolds=52026.020.783—
AutoFeatfolds=52026.020.775—
MALMAS2026.040.775—
OpenFEfolds=52026.020.772—
Baselinefolds=52026.020.771—
DFS2026.040.758—
FAMOSEfolds=52026.020.757—
Base2026.040.756—
AutoFeat2026.040.756—
OpenFE2026.040.755—
OCTree2026.040.754—
TabPFN-HybridActive Learning Strategy=Hybrid, Backbone=TabPFN, Label Budget=100, Batch Size=102026.030.752—
CAAFE2026.040.751—
LLMFE2026.040.748—
TabPFN-Proxy-HybridActive Learning Strategy=Proxy-Hybrid, Backbone=TabPFN, Label Budget=100, Batch Size=102026.030.746—
TabPFN-RandomActive Learning Strategy=Random, Backbone=TabPFN, Label Budget=100, Batch Size=102026.030.743—
TabResNet2026.060.733—
TabPFN-MarginActive Learning Strategy=Margin, Backbone=TabPFN, Label Budget=100, Batch Size=102026.030.724—
TabPFN-CoresetActive Learning Strategy=Coreset, Backbone=TabPFN, Label Budget=100, Batch Size=102026.030.712—
FeatLLMfolds=52026.020.711—
TAROTShot=162026.060.6937—
CatBoost-MarginActive Learning Strategy=Margin, Backbone=CatBoost, Label Budget=100, Batch Size=102026.030.679—
LabelSpreading-RandomActive Learning Strategy=Random, Backbone=LabelSpreading, Label Budget=100, Batch Size=102026.030.648—
XGBoost-MarginActive Learning Strategy=Margin, Backbone=XGBoost, Label Budget=100, Batch Size=102026.030.645—
TAROTShot=82026.060.6294—
TAROTShot=42026.060.6077—
TabLLMShot=162026.060.6038—
SCARFShot=162026.060.5922—
TabPFNShot=162026.060.5891—
STUNTShot=162026.060.5763—
FeatLLMShot=82026.060.5742—
FeatLLMShot=162026.060.566—
TabLLMShot=82026.060.5642—
FeatLLMShot=42026.060.5594—
In-contextShot=162026.060.5529—
SCARFShot=82026.060.5526—
STUNTShot=82026.060.545—
TABLETShot=42026.060.5433—
TabPFNShot=42026.060.54—
In-contextShot=42026.060.5299—
TABLETShot=82026.060.529—
TabNet2026.060.527—
TabPFNShot=82026.060.5258—
In-contextShot=82026.060.5243—
TabLLMShot=42026.060.519—
TABLETShot=162026.060.5165—
SCARFShot=42026.060.4892—
STUNTShot=42026.060.488—
ASK-GBDTHPO=SMAC, Library=Auto-sklearn2021.06—71.191
AutoFeatBackbone=XGBoost, n (number of samples)=1000, p (number of features)=202025.03—75.7
AutoGluonStacking=true2021.06—69.643
BaseBackbone=XGBoost, n (number of samples)=1000, p (number of features)=202025.03—75.1
CAAFEBackbone=XGBoost, n (number of samples)=1000, p (number of features)=202025.03—75.1
CuBASclassifier=k-NN, training_set_sizes=10%–80%2026.07—79.4
Entropyclassifier=k-NN, training_set_sizes=10%–80%2026.07—58.54
FeatLLMBackbone=XGBoost, n (number of samples)=1000, p (number of features)=202025.03—70.7
LLM-FEBackbone=XGBoost, n (number of samples)=1000, p (number of features)=202025.03—76.6
MLP2021.06—69.405
MLP+CRegularization=Cocktails2021.06—74.643
MLP+DRegularization=Dropout2021.06—68.095
NODE2021.06—73.095
OCTreeBackbone=XGBoost, n (number of samples)=1000, p (number of features)=202025.03—75.3
OpenFEBackbone=XGBoost, n (number of samples)=1000, p (number of features)=202025.03—75.8
Randomclassifier=k-NN, training_set_sizes=10%–80%2026.07—59.6
TabNet2021.06—61.19
XGBoostHPO=BOHB2021.06—68.929