kb22/Heart-Disease-Prediction
The project involves training a machine learning model (K Neighbors Classifier) to predict whether someone is suffering from a heart disease with 87% accuracy.
Implements a complete ML pipeline using scikit-learn's KNeighborsClassifier with hyperparameter tuning via GridSearchCV to optimize the k-value selection. The workflow encompasses data preprocessing, feature scaling with StandardScaler, train-test splitting, and model evaluation using confusion matrices and classification metrics. Targets the pandas/scikit-learn ecosystem for rapid prototyping of medical classification tasks.
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MIT
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Last pushed
Mar 28, 2023
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