@article{4360, author = {Beibei Wu}, title = {Practical Evaluation Analysis of Intelligent Product Design Using Decision Tree Algorithm}, journal = {Transactions on Machine Design}, year = {2025}, volume = {13}, number = {1}, doi = {https://doi.org/10.6025/tmd/2025/13/1/9-16}, url = {https://www.dline.info/tmd/fulltext/v13n1/tmdv13n1_2.pdf}, abstract = {The decision tree algorithm is an efficient machine learning technique that can help us better assess the practicality of intelligent products. This paper explores the basic principles of the decision tree algorithm and proposes a series of effective evaluation methods combined with practical applications to achieve better results. Through experimental verification, the decision tree algorithm performs well in the practicality evaluation of intelligent products (using clothing design as an example) and effectively addresses challenges in real-world applications. Therefore, the decision tree algorithm can serve as an effective tool to enhance the quality and competitiveness of product design for businesses.}, }