异常输入输出关联的检测
Detection of Abnormal Input-Output Associations
摘要：
我们研究了一种新的离群点检测问题，旨在识别数据中的异常输入-输出关联，其实例由多维输入（上下文）和输出（响应）对组成。我们提出了我们的方法，通过分析数据的条件（输入-输出）关系空间，捕获的可分解的概率模型。实验结果表明，我们的方法在识别多变量条件离群值的能力。
英文摘要：
We study a novel outlier detection problem that aims to identify abnormal input-output associations in data, whose instances consist of multi-dimensional input (context) and output (responses) pairs. We present our approach that works by analyzing data in the conditional (input--output) relation space, captured by a decomposable probabilistic model. Experimental results demonstrate the ability of our approach in identifying multivariate conditional outliers.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
