Queen Hesti Ramadhamy

COMPARISON OF GAUSSIAN NAIVE BAYES AND RANDOM FOREST FOR ANEMIA CLASSIFICATION USING HEMATOLOGICAL PARAMETERS

Anemia is a global health problem affecting approximately 1.92 billion people, or 24% of the population, according to the WHO. Accurate early detection is crucial for data-driven healthcare. This study evaluates two machine learning algorithms, Gaussian Naive Bayes (GNB) and Random Forest (RF). The classification is ba...