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ANOMALY DETECTION BASED ON RELATIONSHIPS BETWEEN MULTIPLE TIME SERIES

机译:基于多个时间序列之间关系的异常检测

摘要

In some implementations, sequences of time series values determined from machine data are obtained. Each sequence corresponds to a respective time series. A plurality of predictive models is generated for a first time series from the sequences of time series values. Each predictive model is to generate predicted values associated with the first time series using values of a second time series. For each of the plurality of predictive models, an error is determined between the corresponding predicted values and values associated with the first time series. A predictive model is selected for anomaly detection based on the determined error of the predictive model. Transmission is caused of an indication of an anomaly detected using the selected predictive model.
机译:在一些实施方式中,获得从机器数据确定的时间序列值的序列。每个序列对应于各自的时间序列。从时间序列值序列中为第一时间序列生成多个预测模型。每个预测模型将使用第二时间序列的值来生成与第一时间序列相关的预测值。对于多个预测模型中的每一个,在相应的预测值和与第一时间序列相关联的值之间确定误差。基于所确定的预测模型的误差,选择预测模型用于异常检测。传输是由使用所选预测模型检测到异常的指示引起的。

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