RaziyeAkr/heart-attack-classification
In this notebook, I have reviewed several classification algorithms on datasets.
This project helps medical researchers or healthcare analysts compare different methods for predicting heart attacks. It takes in patient health data and outputs a comparison of how accurately various classification algorithms predict heart attack risk, using metrics like accuracy score and F1-score. This is designed for someone evaluating predictive models for health conditions.
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Use this if you need to quickly assess and compare the performance of multiple standard machine learning algorithms for classifying heart attack risk.
Not ideal if you are looking for a ready-to-use application for patient diagnosis or a highly specialized model beyond common classification techniques.
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Aug 22, 2022
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