Iris Flower Classification Model
Key Features: Machine Learning with scikit-learn: The heart of this repository is a machine learning model created using scikit-learn, a widely used machine learning library in Python. It showcases the implementation of a classification algorithm to predict iris flower species based on provided features.
Iris Dataset: The model is trained and tested on the famous Iris dataset, a classic benchmark dataset in machine learning. This dataset contains features like petal length, petal width, sepal length, and sepal width, making it an excellent choice for classification tasks.
Accuracy and Performance: Evaluate the model's performance with metrics like accuracy, precision, recall, and F1-score. Understand how well the model generalizes to new data and its ability to differentiate between iris species.