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Using data mining and judgment analysis to construct a predictive model of crime

机译:使用数据挖掘和判断分析来构建犯罪预测模型

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This paper discusses the use of cognitive psychology and data mining to construct a predictive model of crime. This model predicts from the location, time, and daily mean temperature whether the theft was of a bicycle, a firearm, or a purse. It also discovers the features that were salient to the choice of a target for these three crimes. The model was constructed for Richmond, Virginia. in this analysis association rules were used to construct an independent set of crimes. Then a classification and regression tree methodology was used to create a classification tree. This tree was used in a predictive model that, given the location of the crime, the mean air temperature on that day, and the time ofthe crime, predicted the type of item stolen. The resulting model predicted the object of the theft with accuracy significantly above that of a random draw.
机译:本文讨论了认知心理学和数据挖掘的使用来构建一种预测犯罪模式。该模型从位置,时间和每日平均温度预测盗窃是否是自行车,枪支或钱包。它还发现了这三个犯罪所选择的目标的特征。该模型是为弗吉尼亚州里士满建造的。在此分析中,协会规则用于构建独立的犯罪集。然后使用分类和回归树方法来创建分类树。这棵树用于预测模型,鉴于犯罪的位置,当天的平均空气温度以及犯罪的时间,预测了被盗的物品类型。得到的模型预测了盗窃的对象,精度明显高于随机绘制的精度。

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