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Optimising a model

As each model comprises of separate components, we optimise each component individually. The components in question are:

  • GNN (graph)
  • Classification head (clf_head)
  • Keyword pruning threshold (threshold_optimization)

All separate components can be optimised using the --optimize flag and take three arguments: optimization component, dataset, gnn_type

E.g.:

python main.py --optimize 'clf_head' 'canary' 'GAT'

The additional parameters are those set in the default settings files.

There is a manual optimization for the threshold available as well, specified with threshold_experiment useful for evaluating the effect of the threshold for specific ranges.