LSTM Handling Classifier

Folder structure

lstm_project/
    data/
        dry_laps.csv       ← put your dry CSV here, rename it this
        wet_laps.csv       ← put your wet CSV here, rename it this
    dataset_lstm.py
    model_lstm.py
    train_lstm.py
    test_wet.py

Setup

pip install torch pandas numpy

Step 1 — Train on dry data

python train_lstm.py

This saves the best model to handling_lstm.pth

Step 2 — Test on wet data

python test_wet.py

This loads the dry-trained model and runs it on wet data. The accuracy drop between train validation and wet test is the result.