997 search results - page 1 / 200 » Learning Rule Representations from Boolean Data |
ICANN
2003
Springer
13 years 9 months ago
2003
Springer
We discuss a Probably Approximate Correct (PAC) learning paradigm for Boolean formulas, which we call PAC meditation, where the class of formulas to be learnt is not known in advan...
ECML
2001
Springer
13 years 9 months ago
2001
Springer
Abstract. This paper proposes a generic extension to propositional rule learners to handle multiple-instance data. In a multiple-instance representation, each learning example is r...
GECCO
2009
Springer
13 years 11 months ago
2009
Springer
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
GECCO
2008
Springer
13 years 5 months ago
2008
Springer
Genetic-Based Machine Learning Systems (GBML) are comparable in accuracy with other learning methods. However, efficiency is a significant drawback. This paper presents a new rep...
ICTAI
2007
IEEE
13 years 11 months ago
2007
IEEE
We review a method of generating logical rules, or axioms, from empirical data. This method, using closed set properties of formal concept analysis, has been previously described ...