A fast scalable classifier tightly integrated with RDBMS
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 the approach include its high training speed, linear scalability, and simplicity in implementation. More importantly, the major computation required in the approach can be implemented using standard functions provided by the modern relational DBMS. Besides, with the effective rule pruning strategy, the algorithm proposed in this paper can produce a compact set of classification rules. The results of experiments conducted for performance evaluation and analysis are presented.
classification relational dbms data mining cube operation