Sciweavers

Share
IRI
2008
IEEE

Compound record clustering algorithm for design pattern detection by decision tree learning

8 years 10 months ago
Compound record clustering algorithm for design pattern detection by decision tree learning
Recovering design patterns applied in a system can help refactoring the system. Machine learning algorithms have been successfully applied in mining data patterns. However, one of the main obstacles of applying them for design pattern detection is the difficulty of collecting training examples. Unlike other applications, a design pattern instance typically includes a group of classes with certain relationships. Thus, the possible combinations of the group of classes can be enormous which results in huge training sets making the application of machine learning algorithms impracticable. In this paper, we propose an innovative method using matrix transformations to cluster the training examples. Our method can significantly reduce the size of training examples, thus making it possible to be efficiently applied in machine learning algorithm.
Jing Dong, Yongtao Sun, Yajing Zhao
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where IRI
Authors Jing Dong, Yongtao Sun, Yajing Zhao
Comments (0)
books