Artificial Intelligence and Learning Effects of Reading Classics

This study analyzes the machine learning and deep models that were used to forecast satisfaction effect of classics reading classes. The following main findings comparison their predictive abilities. First, traditional regression model is somewhat low in coefficient determinant. Second, decision tree predicts classes better than model. Third, when we predict effects lessons, support vector show high power with coefficients determination RMSE. Fourth, neural network also higher appropriate epochs batch sizes. Thus, since can more accurately, need adopt using variables.