Hypertension distribution in the original dataset, and balanced class label distribution after applying the Synthetic Minority Oversampling Technique (SMOTE) for training and test data.

مواد مشابهة

• The different models’ performance evaluation using original and SMOTE-adjusted data, including training errors, and validation errors based on characteristics, socioeconomic status, self-awareness and nutritional status among participants aged 34 years and older in Bangladesh from 2011 to 2022.
  حسب: Probir Kumar Ghosh (6947282)
  منشور في: (2025)
• Observational causal association between excessive body weight on hypertension, including crude, adjusted for age, sex, SES, self-awareness by using logistic regression, and Double Machine Learning with Random forest model among participants aged 34 year and older in Bangladesh from 2011 to 2022.
  حسب: Probir Kumar Ghosh (6947282)
  منشور في: (2025)
• Random forest classifier model performance evaluation scores based on characteristics, socioeconomic status (SES), self-awareness and nutritional status among participants aged 34 year and older in Bangladesh from 2011 to 2022.
  حسب: Probir Kumar Ghosh (6947282)
  منشور في: (2025)
• Participant’s characteristics, socioeconomic status (SES), self-awareness and nutritional status among participants aged 34 year and older in Bangladesh from 2011 to 2022.
  حسب: Probir Kumar Ghosh (6947282)
  منشور في: (2025)
• Dependency plot of SHAP values for hypertension, showing the relationship between a feature’s value (X-axis) and its corresponding SHAP value (Y-axis, indicating impact on prediction).
  حسب: Probir Kumar Ghosh (6947282)
  منشور في: (2025)