一个用于预测尼日利亚最高法院判决的数据集
O C Ngige1, F Y Ayankoya2, J A Balogun3
1Federal Institute of Industrial Research, Oshodi, Nigeria.
Data in brief
|August 17, 2023
概括
本研究引入了5585个尼日利亚最高法院案件的结构化数据集,以减少司法程序中的偏见. 这些数据使我们能够使用大数据分析来构建法律案例结果的预测模型.
科学领域:
- 法律信息学 法律信息学
- 计算法 计算法 计算法
- 数据科学在司法中的作用
背景情况:
- 建议大数据分析以减少偏见并增强基于证据的司法程序.
- 尼日利亚最高法院 (SCN) 数据集解决了对结构化法律数据的需求.
研究的目的:
- 策划一个全面的,历史SCN上诉案件的结构化数据集.
- 促进对法律案件结果的预测模型的开发.
- 支持减少司法系统中人类偏见的研究.
主要方法:
- 从SCN在线存储库收集了5585个历史上诉案件.
- 识别和验证了与法庭诉讼有关的13个输入变量和1个输出变量.
- 将结构化非结构化数据转化为电子电子表格格式.
主要成果:
- 创建了5585个刑事和民事SCN上诉案件的结构化数据集.
- 为数值变量生成了描述性的统计总结.
- 该数据集已准备好用于训练预测模型和应用特征提取技术.
结论:
- 开发的数据集为数据驱动的法律研究和偏见减少提供了基础.
- 它可以创建用于司法决策的预测系统.
- 进一步的研究可以利用这一数据集在法律中用于先进的机器学习应用.
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