This project focuses on classifying the species of iris flowers based on their features: sepal length, sepal width, petal length, and petal width. The classification is done using machine learning models trained on the famous Iris dataset.
The goal is to predict the species of an iris flower (setosa, versicolor, or virginica) based on the given features.
The dataset used is the Iris dataset, which is a classic dataset in machine learning. It consists of 150 samples, each having four features:
- Sepal Length (cm)
- Sepal Width (cm)
- Petal Length (cm)
- Petal Width (cm)
Each sample belongs to one of the following classes:
- Iris Setosa
- Iris Versicolor
- Iris Virginica
Dataset Link: https://www.kaggle.com/datasets/uciml/iris