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» Rule Combination in Inductive Learning
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JASIS
2000
143views more  JASIS 2000»
15 years 3 months ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng
CG
2000
Springer
15 years 7 months ago
Chess Neighborhoods, Function Combination, and Reinforcement Learning
Abstract. Over the years, various research projects have attempted to develop a chess program that learns to play well given little prior knowledge beyond the rules of the game. Ea...
Robert Levinson, Ryan Weber
ICML
2005
IEEE
16 years 4 months ago
Learning the structure of Markov logic networks
Markov logic networks (MLNs) combine logic and probability by attaching weights to first-order clauses, and viewing these as templates for features of Markov networks. In this pap...
Stanley Kok, Pedro Domingos
IWCLS
2007
Springer
15 years 9 months ago
Evolving Fuzzy Rules with UCS: Preliminary Results
This paper presents Fuzzy-UCS, a Michigan-style Learning Fuzzy-Classifier System designed for supervised learning tasks. FuzzyUCS combines the generalization capabilities of UCS w...
Albert Orriols-Puig, Jorge Casillas, Ester Bernad&...
ACL
2006
15 years 4 months ago
A Hybrid Relational Approach for WSD - First Results
We present a novel hybrid approach for Word Sense Disambiguation (WSD) which makes use of a relational formalism to represent instances and background knowledge. It is built using...
Lucia Specia