Classification on PHISHING
0.039Empirical RiskAlg. 1
Evaluation results
| Method | Links | ||
|---|---|---|---|
| Alg. 1model=Neural Network, epsilon (ε)=1/√m, K=0.2√m2023.06 | 0.039 | 0.054 | |
| Alg. 1Model=Neural Network, Learning mode=Batch, epsilon=1/sqrt(m)2023.06 | 0.039 | 0.054 | |
| Alg. 1model=Neural Network, epsilon (ε)=1/m, K=0.2√m2023.06 | 0.042 | 0.05 | |
| Alg. 1Model=Neural Network, Learning mode=Batch, epsilon=1/m2023.06 | 0.042 | 0.05 | |
| ERMmodel=Neural Network2023.06 | 0.046 | 0.055 | |
| ERMModel=Neural Network, Learning mode=Batch2023.06 | 0.046 | 0.055 | |
| Alg. 1Model Type=Linear, Learning Setting=Batch, epsilon=1/m, K=0.2√m2023.06 | 0.063 | 0.067 | |
| ERMModel Type=Linear, Learning Setting=Batch2023.06 | 0.064 | 0.067 | |
| Alg. 1Model Type=Linear, Learning Setting=Batch, epsilon=1/√m, K=0.2√m2023.06 | 0.065 | 0.069 | |
| Alg. 2Model architecture=Linear model, Learning protocol=Online learning2023.06 | 0.226 | 0.242 | |
| OGDModel architecture=Linear model, Learning protocol=Online learning2023.06 | 0.226 | 0.22 |