metadata
title: Iris Flower Classifier
emoji: 🌸
colorFrom: purple
colorTo: pink
sdk: gradio
app_file: app.py
pinned: false
license: mit
Iris Flower Classifier
A Random Forest model (scikit-learn) that predicts the species of an iris flower (setosa, versicolor, virginica) from four measurements in centimetres: sepal length, sepal width, petal length and petal width.
- Training data: the classic Iris dataset (150 samples, 3 classes)
- Algorithm: RandomForestClassifier, 100 trees
- Test accuracy: 90% on a 20% hold-out split
Use it in Python
import joblib
from huggingface_hub import hf_hub_download
bundle = joblib.load(hf_hub_download("your-username/iris-classifier", "model.joblib"))
model, classes = bundle["model"], bundle["classes"]
print(classes[model.predict([[5.1, 3.5, 1.4, 0.2]])[0]]) # setosa