基于最大信息系数模型优化的江苏省工业企业指标数据分析

Analysis of industrial enterprise indicator data in Jiangsu Province based on maximum information coefficient model optimization

2023年是《工业互联网创新发展行动计划(2021—2023年)》实施的最后一年。在多重政策背景下,如何通过“互联网+工业大数据”让工业企业对市场需求进行迅速了解并做出相关策略,是目前亟须解决的问题。文章首先介绍数据相关性常用模型,简要分析其特点,然后选取最大信息系数作为数据特征值度量进行模型优化。最后以2022年江苏统计年鉴工业企业主要经济指标作为数据集,得出分析结论。

2023 is the last year of the implementation of the“Industrial Internet Innovation and Development Action Plan(2021-2023)”.In the context of multiple policies,an urgent problem arises of how to enable industrial enterprises to quickly understand the market demand and make relevant strategies through"Internet+industrial big data".This article first introduces common models for data correlation,briefly analyzes their characteristics,and then selects the maximum information coefficient as the data eigenvalue mea-surement for model optimization.Finally,a dataset is compiled based on the main economic indicators of industrial enterprises in the“2022 Jiangsu Statistical Yearbook”,and analytical conclusions are reached.