Harrell‘s C-Index, Concordance C, and C-statistic are all terms used to refer to

最新推荐文章于 2024-06-09 18:16:27 发布

后端工程架构

最新推荐文章于 2024-06-09 18:16:27 发布

阅读量376

点赞数

CC 4.0 BY-SA版权

文章标签： Python

本文链接：https://blog.youkuaiyun.com/HackVibe/article/details/133073949

Python 专栏收录该内容

110 篇文章 ¥59.90 ¥99.00

订阅专栏

C-Index（Harrell's C, Concordance C）是生存分析中评估模型预测准确性的指标，衡量模型对事件发生时间排序的正确率。本文介绍了C-统计量的计算方法，其与AUC的关系，并提供了Python代码示例。" 110910516,10293926,Py-ART：Python气象雷达数据处理工具包解析,"['Python开发', '气象数据处理', '雷达辐射测量', '科学计算库', '数据可视化']

摘要生成于 C知道，由 DeepSeek-R1 满血版支持，前往体验 >

Harrell’s C-Index, Concordance C, and C-statistic are all terms used to refer to the same evaluation metric in survival analysis, which measures the predictive accuracy of a prognostic model. The C-statistic is commonly used in medical research to assess the performance of models that predict the time until an event of interest occurs, such as death or disease recurrence. In this article, we will explore how to calculate the C-statistic, its relationship with the Area Under the Receiver Operating Characteristic Curve (AUC), and provide Python code examples.

C统计量（C-statistic）是生存分析中用于评估预测模型准确性的指标，也被称为Harrell’s C-Index或Concordance C。C统计量常用于医学研究中，用于评估预测模型对特定事件（如死亡或疾病复发）发生时间的预测能力。本文将介绍如何计算C统计量，以及它与接收者操作特征曲线下面积（AUC）之间的关系，并提供Python代码示例。