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Heart Disease Prediction Using Machine Learning Algorithms
- jiang, shu
- Advisor(s): Wu, Ying Nian
Abstract
This paper is focused on the possibility of having heart disease by training four machine learning algorithms. By using the data provided by the UCI Machine Learning Repository, we can analyze and compare the models of logistic regression, random forest, extreme gradient boosting and neural network to choose the most robust model and determine important features in our model.
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