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Iris-Species-Prediction
thiruselvan-mle/Iris-Species-Prediction
Iris-Species-Prediction is a machine learning model from thiruselvan-mle. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model predicts the species of an Iris flower — Setosa, Versicolor, or Virginica — based on its sepal and petal measurements.
Access
Public
Updated Oct 22, 2025
Repo size
5.7 KB
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At a glance
- Access
- Public
- Created
- Oct 22, 2025
- Updated
- Oct 22, 2025
- SHA
- 4950969b
Model card
From the Hugging Face model README
Iris Species Classifier
This model predicts the species of an Iris flower — Setosa, Versicolor, or Virginica — based on its sepal and petal measurements.
Model Details
- Algorithm: Support Vector Classifier (SVC)
- Framework: Scikit-learn
- Accuracy: ~97%
- Dataset: Iris dataset from Kaggle
Input Format
The model expects 4 numerical inputs:
Example: [sepal_length, sepal_width, petal_length, petal_width] = [5.1, 3.5, 1.4, 0.2]
Output
Returns one of:
Iris-setosaIris-versicolorIris-virginica
Usage Example
from huggingface_hub import InferenceClient
client = InferenceClient(model="thiruselvan-mle/Iris-Species-Prediction")
result = client.post(json={"inputs": [5.1, 3.5, 1.4, 0.2]})
print(result)
Author
- Developed by Thiruselvan M
- Project: Iris Species Prediction using Machine Learning
- Created
- Oct 22, 2025
- Updated
- Oct 22, 2025