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Implement various model architectures and options #1
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TODO: combine `data_prep` and `CNN_Model`; Maybe use others models for Time series
Added `transformer_encoder` Achieved 71% accuracy in using `transformer_encoder`
…classification into keras/time+series
…classification into keras/time+series
…ss, added rnn model in keras_model, added a comment in main
Split testing set by 9 subjects
Added Model ensembling Added more running options, e.g. `model`, `ensemble`, `cnn_layers` Updated .gitignore
Enabled accuracy for each subject in model ensembling Refactored CNN+GRU+SimpleRNN model in `cnn_rnn_model`
Optimized code for model ensembling Removed extra keras models Updated directory and naming convention for saved models
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Models:
Options: