Title :
The data mining advisor: meta-learning at the service of practitioners
Author :
Giraud-Carrier, Christophe
Author_Institution :
Dept. of Comput. Sci., Brigham Young Univ., Provo, UT, USA
Abstract :
In order to make machine learning algorithms more usable, our community must be able to design robust systems that offer support to practitioners. In the context of classification, this amounts to developing assistants, which deal with the increasing number of models and techniques, and give advice dynamically on such issues as model selection and method combination. This paper briefly reviews the potential of meta-learning in this context and reports on the early success of a Web-based data mining assistant.
Keywords :
data mining; learning (artificial intelligence); pattern classification; Web-based data mining assistant; data mining advisor; machine learning; metalearning; method combination; model selection; Algorithm design and analysis; Classification algorithms; Computer science; Context modeling; Data mining; Machine learning; Machine learning algorithms; Robustness; Testing;
Conference_Titel :
Machine Learning and Applications, 2005. Proceedings. Fourth International Conference on
Print_ISBN :
0-7695-2495-8
DOI :
10.1109/ICMLA.2005.65