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The Pruning Strategy of Decision Tree of SMT Assembling Quality Control Based on Data Mining

机译:基于数据挖掘的SMT组装质量控制决策树的修剪策略

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Based on the establishment of data warehouse of the decision support model of the SMT assembling quality control, this paper relies its basis on the SLIQ algorithm of the decision tree method of data mining, improves the pruning strategy and conducts a useful exploration on how to form more effective decision-making basis of the quality control system of SMT assembling in order to improve the accuracy and predictability of decision analysis.
机译:基于SMT组装质量控制决策支持模型的数据仓库的建立,本文依赖于数据挖掘决策树方法的SLIQ算法,提高了修剪策略,对如何形成的探索更有效的决策基础SMT组装的质量控制系统,以提高决策分析的准确性和可预测性。

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