Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Petra Vidnerová"'
Autor:
Jan Kalina, Petra Vidnerová
Publikováno v:
Functional and High-Dimensional Statistics and Related Fields ISBN: 9783030477554
Estimation, prediction or smoothing of curves represents a fundamental task of functional data analysis. Nonlinear regression methods allow to search for the best-fit curves explaining the dependence of a response variable on available independent va
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d8dca978ab2735eade6d0503c4908c53
https://doi.org/10.1007/978-3-030-47756-1_20
https://doi.org/10.1007/978-3-030-47756-1_20
Autor:
Jan Kalina, Petra Vidnerová
Publikováno v:
Artificial Intelligence and Soft Computing ISBN: 9783030209117
ICAISC (1)
ICAISC (1)
Radial basis function (RBF) neural networks represent established machine learning tool with various interesting applications to nonlinear regression modeling. However, their performance may be substantially influenced by outlying measurements (outli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8dea7d41cea6672b2d13abe7cac6c759
https://doi.org/10.1007/978-3-030-20912-4_11
https://doi.org/10.1007/978-3-030-20912-4_11
Autor:
Roman Neruda, Petra Vidnerová
Publikováno v:
Advances in Information Technology ISBN: 9783642166983
IAIT
IAIT
Regularization networks are one of the important methods for supervised learning. They benefit from very good theoretical background, though their drawback is the presence of metaparameters. The metaparameters are typically supposed to be given by an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::be9ed1bc4828e1abd07fe7b001d3ebae
https://doi.org/10.1007/978-3-642-16699-0_21
https://doi.org/10.1007/978-3-642-16699-0_21