Features Selection

This code is based on the IJCAI-2018 but can tune easily for other dataset

How to run

• modify the read dataset in FeatureSelection.py

• modify the features combination you want to start with in temp variable in FeatureSelection.py

• modify the useless features in FeatureSelection.py

• add the potential features you want to add in

• select your algorithm and recorded file name

• change the validation in function k_fold in file LRS_SA_RGSS.py

• change the evaluation operator in function ScoreUpdate() in LRS_SA_RGSS.py (> or <)

• run the FeatureSelection.py

• check the record file to see the result

• This code take a while to run, you can stop it any time and restart by replace the best features combination in temp

This features selection method achieved

• 1st in Rong360

  -- https://github.com/duxuhao/rong360-season2

• 12nd in IJCAI-2018 1st round

Algorithm details