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» Results of the KDD'99 Classifier Learning
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ICTAI
2008
IEEE
14 years 2 months ago
Ensemble Learning of Regional Classifiers
We present a new ensemble learning method that employs a set of regional classifiers, each of which learns to handle a subset of the training data. We split the training data and ...
Byungwoo Lee, Yong-chan Na, Byonghwa Oh, Jihoon Ya...
LREC
2008
104views Education» more  LREC 2008»
13 years 9 months ago
Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a ...
Lukasz Degórski, Michal Marcinczuk, Adam Pr...
GECCO
2006
Springer
140views Optimization» more  GECCO 2006»
13 years 11 months ago
A representational ecology for learning classifier systems
The representation used by a learning algorithm introduces a bias which is more or less well-suited to any given learning problem. It is well known that, across all possible probl...
James A. R. Marshall, Tim Kovacs
CEC
2007
IEEE
13 years 11 months ago
Support vector machines for computing action mappings in learning classifier systems
XCS with Computed Action, briefly XCSCA, is a recent extension of XCS to tackle problems involving a large number of discrete actions. In XCSCA the classifier action is computed wi...
Daniele Loiacono, Andrea Marelli, Pier Luca Lanzi
ADBIS
1999
Springer
104views Database» more  ADBIS 1999»
13 years 12 months ago
Arbiter Meta-Learning with Dynamic Selection of Classifiers and Its Experimental Investigation
In data mining, the selection of an appropriate classifier to estimate the value of an unknown attribute for a new instance has an essential impact to the quality of the classifica...
Alexey Tsymbal, Seppo Puuronen, Vagan Y. Terziyan