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Rizquan/HeartAttackPredictionModel

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👤 My Contribution (Group Project)

This repository represents my individual contribution to a university group project on heart attack risk prediction using machine learning.

My Responsibility

Implemented and evaluated the K-Nearest Neighbors (KNN) classification model Performed data preprocessing, including feature scaling and Principal Component Analysis (PCA) to reduce dimensionality and improve distance-based model performance Conducted hyperparameter tuning to identify the optimal K value Evaluated model performance using accuracy, precision, recall, and confusion matrix Analyzed model behavior in a healthcare context with emphasis on minimizing false negatives

Note

The complete project includes contributions from multiple team members. This repository focuses only on my assigned responsibility.

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An end-to-end machine learning project that predicts the risk of heart attack using clinical patient data. This project focuses on building a reliable, interpretable, and healthcare-aware ML pipeline, with special emphasis on minimizing false negatives. This repository contains my individual contribution (KNN implementation) for the group project.

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