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» Evaluating learning algorithms and classifiers
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AAAI
2007
14 years 20 days ago
Cautious Inference in Collective Classification
Collective classification can significantly improve accuracy by exploiting relationships among instances. Although several collective inference procedures have been reported, they...
Luke McDowell, Kalyan Moy Gupta, David W. Aha
GECCO
2000
Springer
14 years 1 months ago
Modeling GA Performance for Control Parameter Optimization
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...
Vincent A. Cicirello, Stephen F. Smith
ECAI
2000
Springer
14 years 2 months ago
Data Set Editing by Ordered Projection
In this paper, an editing algorithm based on the projection of the examples in each dimension is presented. The algorithm, that we have called EOP (Editing by Ordered Projection) h...
Jesús S. Aguilar-Ruiz, José Crist&oa...
ESANN
2006
13 years 11 months ago
Classification by means of Evolutionary Response Surfaces
Abstract. Response surfaces are a powerful tool for both classification and regression as they are able to model many different phenomena and construct complex boundaries between c...
Rafael del Castillo Gomariz, Nicolás Garc&i...
ML
2010
ACM
163views Machine Learning» more  ML 2010»
13 years 5 months ago
Classification with guaranteed probability of error
We introduce a general-purpose learning machine that we call the Guaranteed Error Machine, or GEM, and two learning algorithms, a real GEM algorithm and an ideal GEM algorithm. Th...
Marco C. Campi