private-data-generation
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Different auc with the result
Hi I run demo: python evaluate.py --target-variable='income' --train-data-path=./data/adult_processed_train.csv --test-data-path=./data/adult_processed_test.csv --normalize-data dp-wgan --enable-privacy --sigma=0.8 --target-epsilon=8
But I get very low auc: AUC scores of downstream classifiers on test data : LR: 0.3407119900995038 Random Forest: 0.2610576777879843 Neural Network: 0.3578788366713348 GaussianNB: 0.49315881768882325 GradientBoostingClassifier: 0.2606982987000339
May I know how to run the code to get your listed result?
Another demo on diabete data: AUC scores of downstream classifiers on test data :
LR: 0.5467898193760263
Random Forest: 0.39399288451012593
Neural Network: 0.5228927203065135
GaussianNB: 0.4653694581280788
GradientBoostingClassifier: 0.5630377668308703