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Data Presentation and Application of Machine Learning Methods for Automating Retail Sales Management Processes

机译:自动化零售销售管理流程机器学习方法的数据介绍与应用

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In this paper problem of automation of management retail sales process is discussed. The problem is measurement large data presenting, when data described by a large number of characteristics (features). One of the popular approaches to reducing the feature space dimension is correlation analysis. The correlation analysis results are the list of parameters with strong linear dependencies. Strong linear dependencies placed in this list are not accidental according to the calculated correlation correction. The results of correlation analysis are confirmed with help of a classifier based on random decision trees forests ensemble. Classifier showed that there are no other strong dependencies in the parameters with a weak correlation relation. The results of the analysis were checked by an expert group. Experts confirm results compliance.
机译:在本文讨论了管理零售销售过程的自动化问题。当由大量特征(特征)描述的数据时,问题是测量大数据呈现。减少特征空间尺寸的流行方法之一是相关分析。相关分析结果是具有强线性依赖性的参数列表。根据计算的相关校正,在此列表中放置的强线性依赖项不会偶然。基于随机决策树森林集合的分类器的帮助,确认了相关分析结果。分类器表明,具有较弱关系的参数中没有其他强的依赖关系。专家组检查了分析结果。专家确认业绩合规性。

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