This project demonstrates the implementation of a Decision Tree algorithm for classifying the Iris dataset. The Iris dataset contains three classes of iris plants with four features each.
To get started, clone the repository and install the required dependencies:
git clone https://github.com/yourusername/decision-tree-iris.git
cd decision-tree-iris
pip install -r requirements.txt
- Navigate to the notebooks directory and open the notebook.
- Run the cells sequentially to see the implementation and results of the Decision Tree classifier.
The Decision Tree classifier achieved an accuracy of 100 % on the Iris dataset. Detailed evaluation metrics are provided in the notebook.