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Research on the analysis of regional economic sustainable development trend based on decision tree classification prediction

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  • Shimian Zhang
  • Qingqing Li

Abstract

As China's economic development shifts from the stage of high growth to the stage of high quality development, the methods for regional economic sustainable development trend analysis and prediction become increasingly important. In this study, we propose the optimised TGC4.5, SDC4.5 and SGC4.5 models based on decision tree classification and forecasting C4.5 algorithm, combining Taylor series, GINI index, sequence pairs and dynamic time programming, and optimise the data indicators for regional economic sustainability development trend. The experimental results show that the optimised SDC4.5 optimisation algorithm outperforms C4.5 algorithm in modelling speed, with 8 outperforming C4.5 algorithm and 1 tied in the selected 15 dataset experiments. It outperforms C4.5 algorithm in classification accuracy, with 13 outperforming C4.5 algorithm in the selected 15 dataset experiments. The SDC4.5 algorithm model is faster and more accurate as the decision tree depth increases.

Suggested Citation

  • Shimian Zhang & Qingqing Li, 2023. "Research on the analysis of regional economic sustainable development trend based on decision tree classification prediction," International Journal of Knowledge-Based Development, Inderscience Enterprises Ltd, vol. 13(2/3/4), pages 131-147.
    • Handle: RePEc:ids:ijkbde:v:13:y:2023:i:2/3/4:p:131-147
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