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» An Algorithm for Learning Abductive Rules
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MLDM
2001
Springer
14 years 12 days ago
Concepts Learning with Fuzzy Clustering and Relevance Feedback
Abstractions and Case-Based Reasoning for Medical Course Data: Two Prognostic Applications . . . . . . . . . . . . . . . . . 23 R. Schmidt and L. Gierl Are Case-Based Reasoning and...
Bir Bhanu, Anlei Dong
GECCO
2005
Springer
129views Optimization» more  GECCO 2005»
14 years 1 months ago
Post-processing clustering to reduce XCS variability
XCS is a stochastic algorithm, so it does not guarantee to produce the same results when run with the same input. When interpretability matters, obtaining a single, stable result ...
Flavio Baronti, Alessandro Passaro, Antonina Stari...
ICML
2004
IEEE
14 years 8 months ago
Online and batch learning of pseudo-metrics
We describe and analyze an online algorithm for supervised learning of pseudo-metrics. The algorithm receives pairs of instances and predicts their similarity according to a pseud...
Shai Shalev-Shwartz, Yoram Singer, Andrew Y. Ng
AUSAI
1999
Springer
14 years 7 days ago
Generating Rule Sets from Model Trees
Model trees—decision trees with linear models at the leaf nodes—have recently emerged as an accurate method for numeric prediction that produces understandable models. However,...
Geoffrey Holmes, Mark Hall, Eibe Frank
EGICE
2006
13 years 11 months ago
Evolutionary Generation of Implicative Fuzzy Rules for Design Knowledge Representation
Abstract. In knowledge representation by fuzzy rule based systems two reasoning mechanisms can be distinguished: conjunction-based and implication-based inference. Both approaches ...
Mark Freischlad, Martina Schnellenbach-Held, Torbe...