计算机与现代化

• 数据库与数据挖掘 • 上一篇    下一篇

基于Stacking的社区矫正人员标签生成

  

  1. (华北计算技术研究所系统八部,北京100083)
  • 收稿日期:2019-09-10 出版日期:2020-03-24 发布日期:2020-03-30
  • 作者简介:文晶(1995-),女,江西九江人,硕士研究生,研究方向:大数据挖掘,大数据分析,E-mail: 531344500@qq.com; 郑扬飞(1976-),浙江丽水人,研究员级高工,博士,研究方向:信息化工程,信息系统体系结构,E-mail: zhengyangfei@163.com。
  • 基金资助:
    国家重点研发计划公共安全风险防控与应急技术装备重点专项(司法专题任务)(2018YEFC0831100)

Generation of Community Correctional Personnel Label Based on Stacking

  1. (Dept. 8 of System, North China Institute of Computing Technology, Beijing 100083, China)
  • Received:2019-09-10 Online:2020-03-24 Published:2020-03-30

摘要: 社区矫正人员的规范管理技术平台目前正处于研究阶段,由于实际数据的缺乏,用于构建用户画像的社区矫正人员用户标签生成准确性不够。故本文基于改进的Stacking模型融合算法,对某市司法局的社矫人员数据进行清洗、整理以及特征选择后,进行建模分析,进而得出社矫人员“认罪伏法态度”“对社会的心态”“心理健康状况”“矫正惩戒情况”4个标签的预测结果。通过将预测结果与实验结果对比,得到预测准确率,从而表明Stacking模型融合方法对社区矫正人员用户标签的生成具体有效性和准确性。

关键词: 社区矫正人员, Stacking模型融合, 建模分析, 标签生成

Abstract: The standardized management technology platform for community correctional personnel is in the research stage. Due to the lack of actual data, community correctional personnel tag generation for building user portraits is not accurate enough. Therefore, based on the improved Stacking model fusion algorithm, this paper conducts modeling analysis after cleaning, sorting and feature selection for the community correctional personnel data of a citys judicial bureau. Furthermore, the prediction results of four labels, such as plead guilty attitude, mentality of society, mental health and corrective punishment case, are obtained. Comparing the prediction results with the experimental results, we can get the prediction accuracy. It shows the effectiveness and accuracy of the Stacking model fusion method for the generation of user labels of community correctional personnel.

Key words: community correctional personnel, Stacking model fusion, modeling analysis, tag generation

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