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7 December 2023 Construction of case cause analysis model based on decision tree algorithm
Kunying Li, Yue Li, Kun Xu, Qin Li
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Proceedings Volume 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023); 129410C (2023) https://doi.org/10.1117/12.3011949
Event: Third International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 203), 2023, Yinchuan, China
Abstract
The current analysis model of the causes of cases is generally single objective, and the analysis scope of the causes is small, leading to the increase of analysis deviation. For this reason, a method for constructing a case cause analysis model based on the decision tree algorithm is proposed. According to the current measurement requirements and standards, first determine the source of case cause data, and then build the project of case cause characteristics through pre-processing of case cause data to achieve basic data preparation. Next, design the case cause analysis model, build a multi-level model analysis structure by means of training and evaluation, expand the actual analysis scope, and complete the model construction and ability enhancement. The final test results show that: after three stages of testing and research, the causes of four randomly selected cases were analyzed, and the final real-time analysis deviation value of the model was better controlled below 0.25, indicating that with the aid and support of the decision tree algorithm, the analysis accuracy of the causes of cases has increased, the application ability of the model is better, and has practical application value.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Kunying Li, Yue Li, Kun Xu, and Qin Li "Construction of case cause analysis model based on decision tree algorithm", Proc. SPIE 12941, International Conference on Algorithms, High Performance Computing, and Artificial Intelligence (AHPCAI 2023), 129410C (7 December 2023); https://doi.org/10.1117/12.3011949
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KEYWORDS
Analytical research
Decision trees
Data modeling
Data conversion
Databases
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