Skills Evaluation On Esports Sensors Dataset
Metrics
Accuracy
LogLoss
ROC AUC
Results
Performance results of various models on this benchmark
Model Name | Accuracy | LogLoss | ROC AUC | Paper Title | Repository |
|---|---|---|---|---|---|
| Random Guess | 50 | 0.693 | 0.5 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
| SVM | 85.6 | 0.311 | 0.945 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
| Random Forest | 80 | 0.456 | 0.885 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
| Logistic Regression | 83.8 | 0.596 | 0.886 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
| KNN | 74.1 | 0.442 | 0.899 | Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset | - |
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