Person Re Identification On Esports Sensors
Metrics
Accuracy
LogLoss
ROC AUC
Results
Performance results of various models on this benchmark
Model Name | Accuracy | LogLoss | ROC AUC | Paper Title | Repository |
|---|---|---|---|---|---|
| Logistic Regression | 48.8 | 0.01615 | 0.884 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
| KNN | 41.5 | 0.05735 | 0.84 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
| SVM | 45 | 0.01588 | 0.89 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
| Random Forest | 52.1 | 0.01617 | 0.919 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
| Random Guess | 10 | 0.02303 | 0.5 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
0 of 5 row(s) selected.