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Automatic time series exploration for business intelligence analytics

机译:自动进行时间序列探索以进行商业智能分析

摘要

Techniques are described for generating characterizations of time series data. In one example, a method includes extracting a trend-cycle component, a seasonal component, and an irregular component from a time series of data. The method further includes performing one or more pattern analyzes on the trend-cycle component, the seasonal component, and the irregular component. The method further includes, for each pattern analysis of the one or more pattern analyzes, performing a comparison of an analytic result of the respective pattern analysis to a selected significance threshold for the respective pattern analysis to determine if the analytic result passes the significance threshold for the respective pattern analysis. The method further includes generating an output for each of the analytic results that pass the significance threshold for the respective pattern analysis.
机译:描述了用于生成时间序列数据的表征的技术。在一个示例中,一种方法包括从数据的时间序列中提取趋势周期分量,季节分量和不规则分量。该方法还包括对趋势周期分量,季节分量和不规则分量执行一个或多个模式分析。该方法进一步包括,对于一个或多个模式分析的每个模式分析,将相应模式分析的分析结果与针对相应模式分析的所选重要性阈值进行比较,以确定分析结果是否通过了针对各自的模式分析。该方法还包括为每个分析结果生成输出,该输出通过用于相应模式分析的有效阈值。

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