metadata
license: mit
library_name: sklearn
tags:
- sklearn
- random-forest
- iris
- classification
Iris Classifier
A simple Random Forest classifier trained on the classic Iris dataset.
Model details
- Algorithm: Random Forest (100 trees)
- Library: scikit-learn
- Dataset: Iris (150 samples, 4 features, 3 classes)
- Test accuracy: 1.00
Input
4 numeric features:
- Sepal length (cm)
- Sepal width (cm)
- Petal length (cm)
- Petal width (cm)
Output
Predicted species class: 0 (setosa), 1 (versicolor), or 2 (virginica)
Usage
import skops.io as sio
from huggingface_hub import hf_hub_download
path = hf_hub_download(repo_id="mosesalphonse/iris-classifier", filename="model.skops")
model = sio.load(path, trusted=True)
prediction = model.predict([[5.1, 3.5, 1.4, 0.2]])
print(prediction)