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Research on Solar Term Poetry Evaluation AI System Using Improved Decision Tree Network

The decision tree algorithm is one of the commonly used data classification methods and a relatively mature information mining technology. The logic of its work process is clear, the work efficiency is high, and the data classification has high accuracy. The research data of the evaluation system obtained by the decision tree is easy to understand and implement and has the advantages of high feasibility, high precision, and strong logic. By selecting 30 solar term poems, we used 20 of them as training samples to establish a comprehensive evaluation index model for solar term poems and determine the weights. A solar term poetry evaluation system is also constructed by using an improved decision tree network. The other 10 are used as testing samples. The results show that the horizontal comparison of multiple samples has an accuracy of higher than 80%, and the vertical comparison of a single sample has an accuracy of higher than 88.89%. It is proved that the model can be used as a solar term poetry evaluation system with high accuracy.