基于决策树的供应商全链路动态特征挖掘算法

作者：Zhang Shi-Liang; Sun Gang; Tang Liang-Yun

来源：Journal of Shenyang University of Technology, 2023, 45(4): 447-452.

DOI：10.7688/j.issn.1000-1646.2023.04.15

• data classification
• data preprocessing
• decision tree
• dynamic feature mining
• full link feature
• pruning operation
• RBF neural network
• supplier

In order to reduce the Hamming loss and error rate of feature mining results, a dynamic feature mining algorithm of full supplier link based on decision tree was proposed. The data were numerically discretized and normalized, and the Hamming loss and error rate were reduced by reducing the difference of data range. The decision tree was established by using the processed data, and the accuracy of data classification was improved by pruning. The improved CHI value and RBF neural network were used to effectively mine the dynamic characteristics of the full link. The as-proposed algorithm reduces the Hamming loss and error rate of mining results, and improves the classification processing accuracy and recall rate. The as-proposed algorithm can effectively improve the mining effect of dynamic features of full supplier link. ? 2023 Shenyang University of Technology.

• 单位
  华南理工大学; 南方电网科学研究院有限责任公司