Analyzed CDC diabetes health indicators dataset – Analyzed 253k+ survey records to uncover risk f...Analyzed CDC diabetes health indicators dataset – Analyzed 253k+ survey records to uncover risk f...
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Analyzed CDC diabetes health indicators dataset – Analyzed 253k+ survey records to uncover risk factor patterns; built Decision Tree models with 5-fold cross-validation, achieving 82% classification accuracy. – Optimized model performance through hyperparameter tuning, improving recall of positive diabetes cases by 15%, supporting more accurate early-risk detection insights. – Tech Stack: Python, Pandas, NumPy, Scikit-learn, Seaborn, Matplotlib, Imbalanced-learn
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