Heart-Disease-Prediction and KNN
These are direct competitors—both implement K-Nearest Neighbors classification for heart disease prediction with nearly identical accuracy metrics (~87%), solving the same problem with the same algorithm on comparable datasets.
About Heart-Disease-Prediction
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.
About KNN
eltonvaliyev2008-hub/KNN
Heart Disease Prediction using KNN Classification on 15K+ patient records | 87.5% Accuracy | End-to-End ML Pipeline
Related comparisons
Scores updated daily from GitHub, PyPI, and npm data. How scores work