A python implementation of ID3 decision trees and random forest. The main goal of this repository is to serve as a simple, clean python implementation for people trying to learn the concepts.
The CLI requires three parameters to run:
- path to the train dataset (any csv dataset, where the last column acts as the class label)
- path to the test dataset (any csv dataset, where the last column acts as the class label)
- path to the .cfg file (see examples in the config folder)
Type python main.py -h to see the available options.