相关实验视频
使用人工智能和大数据分析来支持数字经济中的创业决策
1School of Business Management, Jilin University of Finance and Economics, Changchun, 130117, China. 114066@jlufe.edu.cn.
Scientific reports
|October 22, 2025
概括
这项研究评估了机器学习模型,用于在创业中采用人工智能. 梯度提升表现出色,显示公司声誉和位置是关键驱动因素,而不是组织规模.
科学领域:
- 人工智能的人工智能
- 企业家精神的创业精神
- 数据科学数据科学数据科学
背景情况:
- 有限的真实世界数据研究关于创业中的AI.
- 需要解决人工智能研究中的模型解释性和过拟合问题.
- 人工智能在创业中的理论好处需要经验验证.
研究的目的:
- 评估用于预测AI服务重点的机器学习模型.
- 评估人工智能驱动的大数据分析对企业决策的影响.
- 确定数字经济中人工智能采用的关键预测因素.
主要方法:
- 对四种机器学习模型进行比较分析:决策树,随机森林,梯度增强和基于直方图的梯度增强.
- 利用现实世界的数据来预测AI服务重点.
- 通过测试R2评估模型性能,并确定了有影响力的预测因素.
主要成果:
- 梯度提升实现了最高的性能,测试R2为0.9914.
- 公司的声誉和位置被确定为人工智能采用最重要的预测因素.
- 在决策树和随机森林模型中观察到过度装配.
结论:
- 人工智能驱动的大数据分析可以显著减少创业战略中的不确定性.
- 公司的声誉和位置对人工智能采用比组织规模更为关键.
- 调查结果为数字经济的市场进入和投资决策提供了可操作的见解.
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