数据挖掘过程模型分析-毕业论文网 关键字:数据挖掘 数据挖掘过程模型 5A CRISP-DM SEMMA [gap=774]Keywords: Data Mining, Data Mining Process Model, 5A, CRISP-DM, SEMMA
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According to the notion of session mining, a continuous data mining process model is developed for inducing the local first-order rules and inferring higher order rules.
按照挖掘段概念,开发持续挖掘过程模型,用于归纳局部一阶规则与推导高阶规则。
The new data has no classification (in this case, no checks on heart disease have been made) and the scoring process assigns a prediction to each new record according to the mining model.
新的数据没有分类别(这里是指还没有做过心脏病检查),评价过程根据挖掘模型将一个预测赋给每个新的记录。
Furthermore, the paper gives a model of Corporation Competitive Intelligence System based on data mining and its relevant process.
在此基础上提出了一个基于数据挖掘的企业竞争情报系统模型,并介绍了相应的过程。
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