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Stroke Prediction Using Machine Learning by jeeviteshsai37 is a document available to read on EtoBox.
This research paper presents a stacked machine learning approach for predicting stroke occurrences, utilizing feature selection and data preprocessing techniques. The study achieves a predictive accuracy of 98.6% by employing principal component analysis (PCA) and a stacking ensemble method that combines random forest, decision tree, and K-nearest neighbors. The findings highlight the potential of advanced machine learning techniques in improving stroke risk assessment and guiding preventive healthcare stra
- Author
- jeeviteshsai37
- Language
- EN