Fake news generator and detector using keras
The fake news data is from https://github.com/GeorgeMcIntire/fake_real_news_dataset
The deep learning models are implemented in the keras_fake_news_detector/library folder
The demo codes for neural network models implemented for fake new detector can be found in demo and are listed bel:
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LSTM recurrent network with embedding layer
- training: run demo/lstm_classifier_train.py to train and save the model
- predicting: run demo/lstm_classifier_predict.py to load the trained model for prediction
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Feed-forward network with GloVe embedding layer
- training: run demo/glove_ffn_classifier_train.py to train and save the model
- predicting: run demo/glove_ffn_classifier_predict.py to load the trained model for prediction
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Feed-forward network with Doc2Vec that encode the new article and pass as input to the feedforward network
- training: run demo/glove_ffn_classifier_train.py to train and save the model
- predicting: run demo/glove_ffn_classifier_predict.py to load the trained model for prediction
Below are the training history in terms of loss and accuracy for a number of neural network implemented in keras:
