Train model:

python3 main.py --train=True --model_name='multi-rnn' --device_name='iss GPU' --kernel_initializer='he_normal'

Evaluate model:

python3 main.py --train=False --model_name='multi-rnn' --device_name='iss GPU' --kernel_initializer='he_normal'

Ensemble learning, evaluate and visualization:

python3 ensemble.py

Please see details in presentation slides.

Results of ensemble model with He_normal Glorot_uniform and Glorot_normal initializers:

Corresponding Hyperparameters for the best GRU-based model:

Visualization of test label and predictions:

Confusion Matrix:

Normalised confusion matrix: