This project implements a machine learning model to classify iris flowers based on their features using the Decision Tree algorithm. It uses the famous Iris dataset, which includes measurements of various features of three species of iris flowers: Setosa, Versicolor, and Virginica.
- Overview
- Technologies Used
- Installation
- Usage
- Project Structure
- Results
- Future Enhancements
- Contributing
- License
The Iris dataset contains 150 samples of iris flowers, with each sample characterized by four features:
- Sepal length
- Sepal width
- Petal length
- Petal width
The goal of this project is to train a machine learning model to classify the iris flowers into their respective species based on these features.
- Python 3.x
- Pandas
- Scikit-learn
- Matplotlib
- Seaborn
To set up this project, you'll need to install the required libraries. Follow these steps:
- Clone the repository:
git clone https://github.com/chamikamunithunga/iris-flower-classification.git cd iris-flower-classification