HyperAI
HyperAI
Home
Console
Docs
News
Papers
Tutorials
Datasets
Wiki
SOTA
LLM Models
GPU Leaderboard
Events
Search
About
Terms of Service
Privacy Policy
English
HyperAI
HyperAI
Toggle Sidebar
Search the site…
⌘
K
Command Palette
Search for a command to run...
Console
Home
SOTA
Person Re-Identification
Person Re Identification On Esports Sensors
Person Re Identification On Esports Sensors
Metrics
Accuracy
LogLoss
ROC AUC
Results
Performance results of various models on this benchmark
Columns
Model Name
Accuracy
LogLoss
ROC AUC
Paper Title
Random Forest
52.1
0.01617
0.919
Collection and Validation of Psychophysiological Data from Professional and Amateur Players: a Multimodal eSports Dataset
Logistic Regression
48.8
0.01615
0.884
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
KNN
41.5
0.05735
0.84
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.
Previous
Next
Person Re Identification On Esports Sensors | SOTA | HyperAI