📊 Random Forest Classifier on Iris Dataset

This project demonstrates the Random Forest Classifier using Scikit-learn. It applies a supervised machine learning approach to classify the well-known Iris dataset and evaluates the model's accuracy.

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📊 Dataset

• Source: Scikit-learn's built-in Iris dataset
• Features: Sepal Length, Sepal Width, Petal Length, Petal Width
• Target: Setosa, Versicolor, Virginica

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🧠 Model Used

• Algorithm: Random Forest Classifier
• Accuracy: ~96% (depending on random state)
• Evaluation Metrics: Accuracy Score, Confusion Matrix, Classification Report

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⚙️ Tech Stack

• Python
• Scikit-learn

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📸 Output

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👨‍💻 Author

Syed Imthiaz I
B.E. Computer Science and Engineering
KCG College of Technology

🔗 LinkedIn
🔗 LinkedIn Post

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🚫 License & Disclaimer

© 2025 Syed Imthiaz I — All rights reserved. Unauthorized copying, modification, distribution, or use of this code or any part of it is strictly prohibited without the express written permission of the author.

📩 For permission requests, contact: syedimthiaz2006@gmail.com

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