http://www.bibsonomy.org/burst/user/mh/FFOILBibSonomy BuRST Feed for /user/mh/FFOIL2008-10-12T19:31:07+02:00Relational learning and boostinghttp://www.bibsonomy.org/bibtex/2cc01ba6febdfff75007432ecca0ad4da/mhmh2008-04-23T16:38:41+02:00inductive_logic_programming inductive_programming ILP FFOIL FOIL boosting <span style="color:#555555;">J. <a href="http://www.bibsonomy.org/author/Ross Quinlan">Ross Quinlan</a> </span><em>Relational Data Mining, </em><em>chapter 12, </em><em>Springer-Verlag New York, Inc., </em><em>New York, NY, USA, </em>(<em>2001</em>)Wed Apr 23 16:38:41 CEST 2008New York, NY, USARelational Data Mining12292--304Relational learning and boosting2001inductive_logic_programming inductive_programming ILP FFOIL FOIL boosting Boosting, a methodology for constructing and combining multiple classifiers, has been found to lead to substantial improvements in predictive accuracy. Although boosting was formulated in a propositional learning context, the same ideas can be applied to first-order learning (also known as inductive logic programming). Boosting is used here with a system that learns relational definitions of functions. Results show that the occasional negative impact of boosting all resemble the corresponding observations for propositional learning.dblphttp://www.bibsonomy.org/bibtex/20b9bc9dc75c861848fb39da8ecc54b95/mhmh2007-10-24T10:03:06+02:00inductive_logic_programming 1996 inductive_programming ILP FFOIL Quinlan <span style="color:#555555;">J. <a href="http://www.bibsonomy.org/author/Ross Quinlan">Ross Quinlan</a> </span><em>J. Artif. Intell. Res. (JAIR)</em>(<em>1996</em>)Wed Oct 24 10:03:06 CEST 2007J. Artif. Intell. Res. (JAIR)139-161Learning First-Order Definitions of Functions.51996inductive_logic_programming 1996 inductive_programming ILP FFOIL Quinlan