/INF264-project1

Implementation of DecisionTree classifier using numpy and comparison with sklearn implementation.

Primary LanguagePython

INF264-project1

Setup and Requirements

python version used: 3.11

Create a virtual environment and install required packages with: pip install -r requirements.txt

Make sure you have the wine dataset in the project folder. (name should be wine_dataset.csv, unchanged from mittuib)

Set the seed variable in main.py and run the file to replicate results from report.

File structure

Program files:

  • Node.py: class to represent a node in the decision tree

  • DecisionTree.py: python class of decision tree implementation

  • Evaluation.py: class for evaluating different models and parameters

  • main.py: main program to train, evaluate and test models

Report files: (not used for running the program, can be ignored)

  • report.md: only used for generating report
  • images/: images for report
  • data_exploration.ipynb: only used to get images of dataset description