Research Article
Prediction of Ubiquitination Sites Using UbiNets
Table 2
Classification models and their description.
| Models | Model description |
| ub_v1 | Is comprised of a single UbiNet Block |
| ub_deeper | A deeper network, is comprised of 2 UbiNet Blocks |
| ub_deeper_x2 | The deepest UbiNet architecture, is comprised of 3 UbiNet Blocks |
| Dense_residual_v2 | A shallow residual network inspired design |
| 50x2_mlp_elu | 2 hidden layer feed forward network with ELU activation and 50 nodes per hidden layer |
| 100x2_mlp_elu | 2 hidden layer feed forward network with ELU activation and 100 nodes per hidden layer |
| 50x2_mlp_relu | 2 hidden layer feed forward network with ReLU activation and 50 nodes per hidden layer |
| 100x2_mlp_relu | 2 hidden layer feed forward network with ReLU activation and 100 nodes per hidden layer |
| Random forest, 100 estimators | Random forest of 100 metaestimators |
| Random forest, 200 estimators | Random forest of 200 metaestimators |
| gbm, 100 estimators | Gradient Boosting Machine is comprised of 100 metaestimators |
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