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» On learning algorithm selection for classification
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JIFS
2002
107views more  JIFS 2002»
13 years 8 months ago
Model selection via Genetic Algorithms for RBF networks
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
Estefane G. M. de Lacerda, André Carlos Pon...
ICML
2007
IEEE
14 years 9 months ago
CarpeDiem: an algorithm for the fast evaluation of SSL classifiers
In this paper we present a novel algorithm, CarpeDiem. It significantly improves on the time complexity of Viterbi algorithm, preserving the optimality of the result. This fact ha...
Roberto Esposito, Daniele P. Radicioni
ICPR
2004
IEEE
14 years 10 months ago
A Rival Penalized EM Algorithm towards Maximizing Weighted Likelihood for Density Mixture Clustering with Automatic Model Select
How to determine the number of clusters is an intractable problem in clustering analysis. In this paper, we propose a new learning paradigm named Maximum Weighted Likelihood (MwL)...
Yiu-ming Cheung
IJCAI
1989
13 years 10 months ago
An Experimental Comparison of Symbolic and Connectionist Learning Algorithms
Despite the fact that many symbolic and connectionist (neural net) learning algorithms are addressing the same problem of learning from classified examples, very little Is known r...
Raymond J. Mooney, Jude W. Shavlik, Geoffrey G. To...
EUSFLAT
2007
126views Fuzzy Logic» more  EUSFLAT 2007»
13 years 10 months ago
Selecting the Optimal Rule Set Using a Bacterial Evolutionary Algorithm
In many regression learning algorithms for fuzzy rule bases it is not possible to define the error measure to be optimized freely. A possible alternative is the usage of global o...
Mario Drobics, János Botzheim, Klaus-Peter ...