Iris Classification

🤖 Iris classification with Scikit-learn

iris-classification is a simple Python project that demonstrates how to classify the Iris dataset using Scikit-learn. It loads the classic Iris dataset, splits it into training and testing sets, trains a Perceptron model, and evaluates its accuracy and classification report. This project was written for educational purposes, created while learning the basics of machine learning and classification algorithms.

Usage

Setup with Poetry

This project uses Poetry to manage dependencies and virtual environments.

1. Install Poetry (if you don’t have it already):

curl -sSL https://install.python-poetry.org | python3 -

or follow the instructions on the official Poetry site.

2. Clone this repository (or download the code):

git clone https://github.com/ashkanfeyzollahi/iris-classification.git
cd iris-classification

3. Install dependencies and create a virtual environment:

poetry install

This will create a virtual environment and install scikit-learn and any other needed packages.

4. Run the script:

poetry run python iris_classification.py

You should see output showing the accuracy and classification report for the Iris dataset.