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DATA ANOMALY DETECTION METHOD AND APPARATUS, AND ELECTRONIC DEVICE AND STORAGE MEDIUM

机译:数据异常检测方法和装置,以及电子设备和存储介质

摘要

A data anomaly detection method and apparatus, and an electronic device and a computer-readable storage medium. The method comprises: acquiring a standard training data set that includes missing data and an anomaly detection model framework that comprises a variational lower limit function; adjusting the variational lower limit function by using the missing data so as to obtain an optimized variational lower limit function; training the anomaly detection model framework by using the standard training data set so as to obtain an anomaly detection model; performing, by using the anomaly detection model, detection on a data set to be subjected to detection and obtaining a reconstruction probability of data to be tested; and if there is target data to be tested with a reconstruction probability greater than or equal to a reconstruction threshold value, determining that the target data to be tested is abnormal data. By means of the method, the efficiency and accuracy of key performance indicator (KPI) anomaly detection can be improved.
机译:数据异常检测方法和装置,以及电子设备和计算机可读存储介质。该方法包括:获取包括缺少数据和异常检测模型框架的标准训练数据集,包括变分下限功能;通过使用缺失的数据调整变分的下限功能,以获得优化的变分下限功能;通过使用标准训练数据集培训异常检测模型框架,以获得异常检测模型;通过使用异常检测模型执行,检测要进行检测的数据集,并获得要测试的数据的重建概率;如果存在要测试的重建概率大于或等于重建阈值的目标数据,则确定要测试的目标数据是异常数据。通过该方法,可以提高关键性能指标(KPI)异常检测的效率和准确性。

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