It is a deep learning model (LSTM) for the classification of two classes (each class has two features), which was applied to a large dataset.
It has consisted three phases:
- Labeling phase, which is based on our desirable features.
- Preprocessing, involves making windows (according to our desirable step size) and class balancing.
- Training our LSTM model and testing its performance.