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固定专家组的广义协议统计

Generalized Agreement Statistics over Fixed Group of Experts
课程网址: http://videolectures.net/ecmlpkdd2011_shah_statistics/  
主讲教师: Mohak Shah
开课单位: 北美博世研究与技术中心
开课时间: 2011-11-30
课程语种: 英语
中文简介:
机会校正统计数据的推广用于衡量数据实例的类别标签分配的互联网协议,传统上依赖于可变专家组的边际化论证。此外,这一论点还导致了协议措施,以评估孤立分类器对由专家组分配的(多个)标签的类别预测。我们表明这些措施不一定适用于更典型的固定专家组场景。我们还提出了新的,更有意义的,更少变量的推广,用于量化固定组间的专家间协议,并通过考虑专家特定的偏差和相关性,在多个专家类多方案中评估分类器的输出。
课程简介: Generalizations of chance corrected statistics to measure interexpert agreement on class label assignments to the data instances have traditionally relied on the marginalization argument over a variable group of experts. Further, this argument has also resulted in agreement measures to evaluate the class predictions by an isolated classifier against the (multiple) labels assigned by the group of experts. We show that these measures are not necessarily suitable for application in the more typical fixed experts' group scenario. We also propose novel, moremeaningful, less variable generalizations for quantifying both the inter-expert agreement over the fixed group and assessing a classifier's output against it in a multiexpert multi-class scenario by taking into account expert-specific biases and correlations.
关 键 词: 机会校正; 互联网协议; 孤立分类器
课程来源: 视频讲座网
最后编审: 2019-04-03:lxf
阅读次数: 35