文章基本信息

标题：Hybrid Data Mining Technique for Knowledge Discovery from Engineering Materials Data Sets
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作者：Doreswamy ; Hemanth K S
期刊名称：International Journal of Database Management Systems
印刷版ISSN：0975-5985
电子版ISSN：0975-5705
出版年度：2011
卷号：3
期号：1
DOI：10.5121/ijdms.2011.3111
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Studying materials informatics from a data mining perspective can be beneficial for manufacturing and other industrial engineering applications. Predictive data mining technique and machine learning algorithm are combined to design a knowledge discovery system for the selection of engineering materials that meet the design specifications. Predictive method-Naive Bayesian classifier and Machine learning Algorithm - Pearson correlation coefficient method were implemented respectively for materials classification and selection. The knowledge extracted from the engineering materials data sets is proposed for effective decision making in advanced engineering materials design applications.
关键词：Naive Bayesian Classifier; Person Correlation Analysis; Knowledge Discovery; Materials informatics.