%0 Conference Paper %1 kdml1 %A Janssen, Frederik %A Fürnkranz., Johannes %B Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen & Adaptivitaet %C Kassel, Germany %D 2010 %E Atzmüller, Martin %E Benz, Dominik %E Hotho, Andreas %E Stumme, Gerd %K clustering learning regression room:0446 rule separate-and-conquer session:kdml1 workshop:kdml %T Separate-and-conquer Regression %U http://www.kde.cs.uni-kassel.de/conf/lwa10/papers/kdml1.pdf %X In this paper a rule learning algorithm for the prediction of a numerical target variable is presented. It is based on the separate-and-conquer strategy and the classification phase is done by a decision list. A new splitpoint generation method is introduced for the efficient handling of numerical attributes. It is shown that the algorithm performs comparable to other regression algorithms where some of them are based on rules and some are not. Additionally a novel heuristic for evaluating the trade-off between consistency and generality of regression rules is introduced. This heuristic features a parameter to directly trade off the rules consistency and its generality. We present an optimal setting for this parameter based on an optimization on several data sets.

@inproceedings{kdml1, abstract = {In this paper a rule learning algorithm for the prediction of a numerical target variable is presented. It is based on the separate-and-conquer strategy and the classification phase is done by a decision list. A new splitpoint generation method is introduced for the efficient handling of numerical attributes. It is shown that the algorithm performs comparable to other regression algorithms where some of them are based on rules and some are not. Additionally a novel heuristic for evaluating the trade-off between consistency and generality of regression rules is introduced. This heuristic features a parameter to directly trade off the rules consistency and its generality. We present an optimal setting for this parameter based on an optimization on several data sets.}, added-at = {2010-10-05T14:15:12.000+0200}, address = {Kassel, Germany}, author = {Janssen, Frederik and Fürnkranz., Johannes}, biburl = {https://www.bibsonomy.org/bibtex/24b6e1f8214d6edf670b11a569a5762de/lwa2010}, booktitle = {Proceedings of LWA2010 - Workshop-Woche: Lernen, Wissen {\&} Adaptivitaet}, crossref = {lwa2010}, editor = {Atzmüller, Martin and Benz, Dominik and Hotho, Andreas and Stumme, Gerd}, interhash = {eb5e9033b4263e872fa7a598808de851}, intrahash = {4b6e1f8214d6edf670b11a569a5762de}, keywords = {clustering learning regression room:0446 rule separate-and-conquer session:kdml1 workshop:kdml}, presentation_end = {2010-10-04 15:52:30}, presentation_start = {2010-10-04 15:30:00}, room = {0446}, session = {kdml1}, timestamp = {2010-10-05T14:15:14.000+0200}, title = {Separate-and-conquer Regression}, track = {kdml}, url = {http://www.kde.cs.uni-kassel.de/conf/lwa10/papers/kdml1.pdf}, year = 2010 }