A-Comparative-Machine-Learning-Framework-for-Heart-Attack-Risk-Prediction-Using-Data-Preprocessing
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This project presents a comparative machine learning framework for heart attack risk prediction using Python. It includes data preprocessing, feature engineering, SMOTE for class balancing, cross validation, and performance evaluation of multiple ML models.
Description provenance: Original source
Measured: Sep 24, 2026 · 6 observations
Source evidence
- Source
- GitHub
- Last activity
- Aug 29, 2026
- observations
- 6
Fit to your task has not been evaluated.
Comparable readings are grouped by signal and unit.
Measured signals
- Stars
- 60
- stars
- Measured · Sep 24, 2026
Momentum
- momentum score
- 15.3
- Window
- 7 days
- Absolute change
- +1
- Relative change
- +1.69%
- Public signals
- Measured
Domains & Uses
- Domains
- Data engineering
Measurement history
Comparable readings are grouped by signal and unit.
Stars
stars
Time
Exact values
| Measured | Public signals |
|---|---|
| Sep 19, 2026 | 59 stars |
| Sep 20, 2026 | 59 stars |
| Sep 21, 2026 | 60 stars |
| Sep 22, 2026 | 60 stars |
| Sep 23, 2026 | 60 stars |
| Sep 24, 2026 | 60 stars |
Classifications
- Nature
- Resource