Classification on Hepmass
88.8AccuracyFlowGMM
Evaluation results
| Method | Links | |
|---|---|---|
| FlowGMMn_l=20, n_u=140k, classes=2, training=semi-supervised2019.12 | 88.8 | |
| Π-modeln_l=20, n_u=140k, classes=2, training=semi-supervised2019.12 | 87.9 | |
| kNN Label Spreadingn_l=20, n_u=140k, classes=2, training=semi-supervised2019.12 | 87.2 | |
| RBF Label Spreadingn_l=20, n_u=140k, classes=2, training=semi-supervised2019.12 | 87.1 | |
| Logistic Regressionn_l=20, n_u=140k, classes=2, training=labeled data only2019.12 | 84.9 | |
| kNNn_l=20, n_u=140k, classes=2, training=labeled data only2019.12 | 84.6 | |
| 3-Layer NN + Dropoutn_l=20, n_u=140k, classes=2, training=labeled data only2019.12 | 84.4 |