Symbolic Machine Learning Systems
Mostrando 1-3 de 3 artigos, teses e dissertações.
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1. Extraction of knowledge from Artificial Neural Networks using Symbolic Machine Learning Systems and Genetic Algorithm / "Extração de conhecimento de redes neurais artificiais utilizando sistemas de aprendizado simbólico e algoritmos genéticos"
In Machine Learning - ML there is not a single algorithm that is the best for all application domains. In practice, several research works have shown that Artificial Neural Networks - ANNs have an appropriate inductive bias for several domains. Thus, ANNs have been applied to a number of data sets with high predictive accuracy. Symbolic ML algorithms have a
Publicado em: 2003
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2. Um ambiente para avaliação de algoritmos de aprendizado de máquina simbólico utilizando exemplos. / An environment to evaluate machine learning algorithms.
A learning system is a computer program that makes decisions based on the accumulative experience contained in successfully solved cases. The classification rules induced by a learning system are judged by two criteria: their classification error on an independent test set and their complexity. Practical learning systems have been developed using different p
Publicado em: 1997
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3. A dynamical systems perspective on the relationship between symbolic and non-symbolic computation
It has been claimed that connectionist (artificial neural network) models of language processing, which do not appear to employ “rules”, are doing something different in kind from classical symbol processing models, which treat “rules” as atoms (e.g., McClelland and Patterson in Trends Cogn Sci 6(11):465–472, 2002). This claim is hard to assess in
Springer Netherlands.