Related Issues (20)
- Evaluate FakeGAN on the OpSpam dataset
- Create informational badges for individual reviews based on the statistical data
- Create informational badges for each of the results sections
- Stretch: Create visualizations for user badges
- Tweak hyperparameters of LSTM networks based on research HOT 5
- Tweak hyperparameters of CNN based on research HOT 6
- Complete an entire first draft of the paper
- Run SeqGAN on Yelp data
- Improve Frontend Performance
- Compute reviewer data using entire dataset
- Model Selector
- Lucas Score reflecting modified confidence score
- User Testing
- Implement PyTorch BERT for result validation HOT 3
- Begin adding results to paper
- Do an experiment on split sentiment data with SVM and (BEST_NEURAL_CLASSIFIER).
- Validate BERT OpSpam TensorFlow accuracy
- Add endpoints to LUCAS API for Lucify frontend (Best candidates of experiments)
- Run BERT on yelp data including user features
- Plan and rehearse final demo
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from lucas.