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- Hyper_basis_function_network abstract "In machine learning, a Hyper basis function network, or HyperBF network, is a generalization of radial basis function (RBF) networks concept, where the Mahalanobis-like distance is used instead of Euclidian distance measure. Hyper basis function networks were first introduced by Poggio and Girosi in the 1990 paper “Networks for Approximation and Learning”.".
- Hyper_basis_function_network wikiPageID "44738576".
- Hyper_basis_function_network wikiPageRevisionID "639789164".
- Hyper_basis_function_network subject Category:Artificial_neural_networks.
- Hyper_basis_function_network subject Category:Classification_algorithms.
- Hyper_basis_function_network subject Category:Machine_learning_algorithms.
- Hyper_basis_function_network comment "In machine learning, a Hyper basis function network, or HyperBF network, is a generalization of radial basis function (RBF) networks concept, where the Mahalanobis-like distance is used instead of Euclidian distance measure. Hyper basis function networks were first introduced by Poggio and Girosi in the 1990 paper “Networks for Approximation and Learning”.".
- Hyper_basis_function_network label "Hyper basis function network".
- Hyper_basis_function_network sameAs m.012hfz_9.
- Hyper_basis_function_network wasDerivedFrom Hyper_basis_function_network?oldid=639789164.
- Hyper_basis_function_network isPrimaryTopicOf Hyper_basis_function_network.