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

Abstract:

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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.

Info:

Periodical:

Advanced Materials Research (Volumes 204-210)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

704-707

DOI:

10.4028/www.scientific.net/AMR.204-210.704

Citation:

H. Jiang et al., "The Pruning Strategy of Decision Tree of SMT Assembling Quality Control Based on Data Mining", Advanced Materials Research, Vols. 204-210, pp. 704-707, 2011

Online since:

February 2011

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Price:

$35.00

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