This project demonstrates the application of machine learning in classifying iris flowers. It serves as an accessible introduction to data science and classification methods with a Jupyter Notebook.
- Iris Species: The dataset consists of iris flowers, specifically from the species setosa, versicolor, and virginica.
- Key Measurements: The essential characteristics used for classification include sepal length, sepal width, petal length, and petal width.
- Machine Learning Model: The project involves the creation and training of a machine learning model to accurately classify iris flowers based on their measurements.
| Modèle | Précision | Recall | F1 Score |
|---|---|---|---|
| Random Forest | 0.95 | 0.94 | 0.94 |
| Support Vector Machine | 0.92 | 0.90 | 0.91 |
| K-Nearest Neighbors(K=3) | 0.89 | 0.88 | 0.88 |
| Decision trees | 0.89 | 0.88 | 0.88 |