Hypertension detection via tree-based stack ensemble with smote-tomek data balance and xgboost meta-learner

HIGHLIGHTS

• What: To curb these issues the study explores the tree-based stacking ensemble with Decision tree Adaptive Boosting and Random Forest (base learners) while the authors explore the as a With the Kaggle dataset as retrieved the stacking ensemble yields a prediction accuracy of 1.00 and an F1-score of 1.00 that effectively correctly classified all instances of the test dataset.
• Who: Moses De Rosal from the Department of Computer Science, Dennis Osadebay University Asaba, Nigeria have published the Article: Type of the Paper (Article, in the Journal: (JOURNAL)
• How: The . . .
  

   

  

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