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Smart Education: Predictive Analytics of Student Academic Performance Using Machine Learning Models Bayes, Random Forest, Random Tree, Linear Regression, Logistic Regression, k-Nearest Neighbors, Multilayer Perceptron, J48, and Decision Stump models. The evaluation criteria for predictive analytics included Correlation Coefficient, Mean Absolute Error, Mean Absolute Percentage Error, Root Mean Squ预知 发表于 2025-3-28 22:57:16
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