【摘 要】
：
In this paper, we report our success in building efficient scalable classifiers by exploring the capabilities of modern relational database management systems(R
【机 构】
：
School of Economics and Management,Department of Computer Science
【基金项目】
：
面向21世纪教育振兴行动计划(985计划)
论文部分内容阅读
In this paper, we report our success in building efficient scalable classifiers by exploring the capabilities of modern relational database management systems(RDBMS).In addition to high classification accuracy, the unique features of theapproach include its high training speed, linear scalability, and simplicity in implementation. More importantly,the major computation required in the approachcan be implemented using standard functions provided by the modern relational DBMS.Besides, with the effective rule pruning strategy, the algorithm proposed inthis paper can produce a compact set of classification rules. The results of experiments conducted for performance evaluation and analysis are presented.
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