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FORS

swMATH ID: 4848
Software Authors: Karalić, Aram; Bratko, Ivan
Description: A new approach developed in ILP, called First Order Regression (FOR), is a combination of ILP and numerical regression. First-order logic descriptions are induced to carve out those subspaces that are amenable to numerical regression among real-valued variables. The program FORS (First Order Regression System) is an implementation of this idea, where numerical regression is focused on a distinguished continuous argument of the target predicate. This can be viewed as a generalisation of the usual ILP problem. Namely, the target predicate in usual ILP can be modified by adding an extra ”continuous” attribute whose value would be determined by the truth of the examples: 1.0 for positive examples and 0.0 for negative. The regression formulas would only involve this attribute and FORS would tend to find rules that cover subsets of positive-only and negative-only examples.
Homepage: http://www-ai.ijs.si/~ilpnet2/systems/fors.html
Programming Languages: C mixed with SICStus Prolog
Operating Systems: None
Dependencies: None
Keywords: first-order regression; inductive logic programming
Related Software: UCI-ml; C4.5; GOLEM; Aleph; shap; JDQZ; LIBLINEAR; JDQR; ReliefF; MALSAR; MULAN; Orange4WS; nFOIL; gBoost; kFOIL; Pegasos; FOIL
Referenced in: 13 Publications

Standard Articles

1 Publication describing the Software, including 1 Publication in zbMATH Year
First order regression. Zbl 0866.68089
Karalić, Aram; Bratko, Ivan
1997

Referencing Publications by Year