Ancient glass classification based on random forest algorithm and decision tree model

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The texture change of ancient glass depends on its chemical composition and preservation environment, and it is highly susceptible to weathering by the burial environment. In this paper, a classification model based on random forest algorithm is established to solve the problem of analyzing the classification laws of high potassium glass and lead-barium glass; a decision tree model based on decision tree is established to solve the problem of subclass differentiation of glass categories and analyzing their rationality and sensitivity. The reasonableness of the model and the accuracy of the data are tested by the plain Bayesian algorithm.