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The sequence of execution

Active learning with Fast iteration

  1. Step 1 (source):
  • get the source features
python3 step1_save_feat_source.py
  • cluster the source anchors
python3 step1_cluster_anchors_source.py: 
  • select active samples with ratio of 0.01
python3 step1_select_active_samples.py: 
  • train stage1 model
python3 step1_train_active_suponly.py
  1. Step 2 (iterate for n times in target):
  • get the target features
python3 step2_n_save_feat_target.py
  • cluster the target anchors
python3 step2_n_cluster_anchors_source.py: 
  • additionally select active samples
python3 step2_n_select_active_samples.py: 
  • train model
python3 step1_train_active_suponly.py