📊 Showing 2 results | 📏 Metric: AUC
Rank | Model | Paper | AUC | Date | Code |
---|---|---|---|---|---|
1 | Random Forest | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | 98.65 | 2022-10-25 | 📦 ajaychawda58/uadad |
2 | Gradient Boosting | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | 95.88 | 2022-10-25 | 📦 ajaychawda58/uadad |