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ResearchFormerly WizWand

Classification on Protein (test)

99.07AccuracySklearn
30.398848.226966.05583.8831Oct 1, 2021Jul 8, 2022Apr 14, 2023Jan 19, 2024Oct 25, 2024Aug 1, 2025May 8, 2026
Updated 5mo ago

Evaluation results

MethodLinks
SklearnModel architecture=Linear model, Loss function=Logistic regression, Solver=L-BFGS2022.0599.07
Cross-entropyModel architecture=Linear model, Loss function=Cross-entropy2022.0598.89
HingeModel architecture=Linear model, Loss function=Hinge2022.0597.69
EXACTModel architecture=Linear model, Loss function=EXACT2022.0597.69
Re-training from Scratchre-training=true2023.0469.64
ANT-HardTraining Time=12s, Number of Seeds=102026.0568.81
ANT-SoftNumber of Seeds=102026.0568.81
DTSemNetNf=357, Nc=3, Ns=14895, Height=42026.0568.6
DTSemNetTraining Time=43s, Number of Seeds=102026.0568.6
TAONf=357, Nc=3, Ns=14895, Height=42026.0568.41
DGTNf=357, Nc=3, Ns=14895, Height=42026.0567.8
GARE/MetaFPPre-trained Task=Photo (Product Category Prediction), Pre-trained Accuracy=0.95612023.0460.71
GARE/MetaFPPre-trained Task=Cora (Publication Classification), Pre-trained Accuracy=0.91212023.0458.93
CARTNf=357, Nc=3, Ns=14895, Height=no predefined height2026.0557.53
TnT#S=692021.1057.26
CART#S=762021.1055.3
Vanilla ReusingPre-trained Task=Cora (Publication Classification), Pre-trained Accuracy=0.91212023.0440.18
Vanilla ReusingPre-trained Task=Photo (Product Category Prediction), Pre-trained Accuracy=0.95612023.0433.04