Unsupervised Anomaly Detection On Vehicle
评估指标
AUC
评测结果
各个模型在此基准测试上的表现结果
模型名称 | AUC | Paper Title | Repository |
---|---|---|---|
NeuTraL-AD | 57.03 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | |
SOM | 65.43 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | |
RSRAE | 55.38 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | |
Latent Outlier Exposure | 58.59 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | |
Isolation Forest | 59.42 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | |
One Class Support Vector Machines | 51.68 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | |
Local Outlier Factor | 52.86 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | |
DAGMM | 51.22 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings | |
SOM-DAGMM | 53.82 | Unsupervised Anomaly Detection for Auditing Data and Impact of Categorical Encodings |
0 of 9 row(s) selected.