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Analyzing mining pattern evolutions by comparing labels, algorithms, or data patterns chosen by a reasoning component

机译:通过比较推理组件选择的标签,算法或数据模式来分析挖掘模式的演变

摘要

Architecture for analyzing pattern shifts in data patterns of data mining models and outputting the results. This allows comparing and describing differences between two semantically similar sets of patterns (or mining models), and for analyzing historical changes in versions of the same model or differences in patterns found by two or more different algorithms applied to the same data. The architecture can also facilitate explaining data patterns that shift over time and over different data populations, and between versions of the same model that use different algorithms. A model component is employed for storing data mining models have respective sets of data patterns obtained from a dataset, and an analysis component analyzes the sets of the data patterns for difference data therebetween. The dataset can be a subsample of a larger set of data and can be analyzed by the analysis component over a time period.
机译:用于分析数据挖掘模型的数据模式中的模式转换并输出结果的体系结构。这允许比较和描述两个语义相似的模式集(或挖掘模型)之间的差异,并用于分析同一模型版本的历史变化或通过应用于相同数据的两种或多种不同算法发现的模式差异。该体系结构还可以帮助解释随着时间推移和不同数据填充量以及使用不同算法的同一模型版本之间的数据模式。使用模型组件来存储数据挖掘模型,这些模型具有从数据集中获得的各个数据模式集,而分析组件则分析数据模式集之间的差异数据。数据集可以是较大数据集的子样本,并且可以由分析组件在一段时间内进行分析。

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