多维数据的统计变化检测][Statistical Change Detection for Multi-Dimensional Data ]

多维数据的统计变化检测 Statistical Change Detection for Multi-Dimensional Data


课程网址:	http://videolectures.net/kdd07_song_scd/
主讲教师:	Xiuyao Song
开课单位:	佛罗里达大学
开课时间:	2007-08-15
课程语种:	英语
中文简介:	本文研究检测多维数据集中的分布变化。对于给定的基线数据集和一组新观察到的数据点，我们定义了一个称为密度测试的统计测试，用于确定观察到的数据点是否来自产生基线数据集的基础分布。我们定义了一个在零假设下严格分配的测试统计量。我们的实验结果表明，密度测试比现有的两种多维变化检测方法具有更大的功率。
课程简介:	This paper deals with detecting change of distribution in multi-dimensional data sets. For a given baseline data set and a set of newly observed data points, we define a statistical test called the density test for deciding if the observed data points are sampled from the underlying distribution that produced the baseline data set. We define a test statistic that is strictly distribution-free under the null hypothesis. Our experimental results show that the density test has substantially more power than the two existing methods for multi-dimensional change detection.
关键词:	多维数据; 密度测试; 统计测试
课程来源:	视频讲座网
最后编审:	2019-05-09：lxf
阅读次数:	137

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