random-forest-train

The random-forest-train app is a toy case implementation of a random forest classifier.
It uses a 20% train-test split to evaluate the performance of the model.
The script requires three arguments: a CSV file containing features (without header), another CSV file containing the corresponding classes (single column without header), and the output path where to save the trained model.