🧠 Breast Cancer Diagnosis using KNN

A simple machine learning comparison project between:

• ✅ Manual K-Nearest Neighbors implementation
• ✅ Scikit-learn’s KNeighborsClassifier

Both models are tested on breast cancer diagnostic data and compared using accuracy and visualization.

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📦 Features Used

• Tumor features: radius, texture, perimeter, area, etc.
• Binary labels: Malignant (1) or Benign (0)

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🔍 Results

Model	Accuracy
Manual KNN	~91.2%
Sklearn KNN	~95.6%

📊 A visual comparison is provided in the final plot.

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▶️ How to Run

# Clone the repo
git clone https://github.com/yourusername/Breast-Cancer-KNN-Comparison.git
cd Breast-Cancer-KNN-Comparison

# Install dependencies
pip install -r requirements.txt

# Run the model
python breast_cancer_knn.py

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🧑‍💻 Author

Mohammed Asaad
📧 mo.asaad999@gmail.com
🔗 LinkedIn

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⚖️ License

This project is licensed under the MIT License.