Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern dis- covery algorithms employ exhaustive search.

18 дек. 2013 г. · Unlike previous results that demonstrated that rule learning algorithms suffer from over-searching, our work pays particular attention to the ...

In this paper, we evaluate the spectrum of dierent search strategies to see whether separate-and-conquer rule learning algorithms are able to gain performance ...

A Re-Evaluation of the Over-Searching. Phenomenon in Inductive Rule Learning. Frederik Janssen. Johannes Fürnkranz. October 6, 2008 ' KDML 2008 ' Janssen ...

In this paper, we evaluate the spectrum of different search strategies to see whether separate-and-conquer rule learning algorithms are able to gain performance ...

Abstract. Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern dis-.

Type of publication: Inproceedings ; Citation: jf:SDM-09 ; Booktitle: Proceedings of the SIAM International Conference on Data Mining (SDM-09) ; Year: 2009 ; Pages: ...

26 авг. 2018 г. · A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. Konferenzveröffentlichung, Bibliographie. URL / URN: http://www ...

A re-evaluation of the over-searching phenomenon in inductive rule learning. F Janssen, J Fürnkranz. Proceedings of the 2009 SIAM International Conference on ...

25 апр. 2024 г. · A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning. SDM 2009: 329-340. [e1]. view. table of contents in dblp; no ...