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Multiple Regression01:25

Multiple Regression

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Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
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自动划船事件分配:一种机器学习方法.

Yumeng Li1, Rachel M Koldenhoven1, Nigel C Jiwan2

  • 1Department of Health and Human Performance, Texas State University, San Marcos, TX, USA.

Sports biomechanics
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概括

机器学习模型使用人口统计和动力学准确地将精英划船员分配到事件中. 这种数据驱动的方法增强了运动员的选择,通过减少主观偏见来优化团队表现.

关键词:
划船动力学 划船动力学人工智能的人工智能是人工智能.这是分类分类的分类.协调 协调 协调 协调运动表现体育表现体育表现

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科学领域:

  • 运动科学 运动科学 运动科学
  • 生物力学 生物力学
  • 机器学习 机器学习

背景情况:

  • 精英划船的表现取决于匹配运动员的能力与事件需求.
  • 目标运动员分类对于优化团队组成和成功至关重要.

研究的目的:

  • 开发和评估机器学习模型,用于将划船员分配到特定的划船赛事.
  • 为了利用人口统计和动力学数据进行客观的划船员分类.

主要方法:

  • 采集了55名精英划船员的3D运动数据 (干,上臂) 在使用惯性测量单位系统的三次冲击速度.
  • 使用矢量编码分析了分段和关节的运动范围和运动协调.
  • 在人口和动态数据上训练了六个监督机器学习模型.

主要成果:

  • 机器学习模型成功地将划船者分为事件组 (合八对单/对).
  • 顶级模型 (决策树,极端梯度提升,随机森林) 实现了高准确率 (0.89-0.93).

结论:

  • 通过机器学习自动分配划船赛事,为教练提供客观的决策工具.
  • 这种方法最大限度地减少了主观偏见,提高了运动员选择的公平性和准确性.
  • 通过数据驱动的洞察力优化团队组成可以提高整体绩效结果.