Mathematical Research Data Initiative
Main page
Recent changes
Random page
Help about MediaWiki
Create a new Item
Create a new Property
Create a new EntitySchema
Merge two items
In other projects
Discussion
View source
View history
Purge
English
Log in

A meta-learning method to select the kernel width in support vector regression

From MaRDI portal
Publication:703049
Jump to:navigation, search

DOI10.1023/B:MACH.0000015879.28004.9bzbMath1101.68083OpenAlexW1989048657MaRDI QIDQ703049

D. Kharzeev

Publication date: 19 January 2005

Published in: Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1023/b:mach.0000015879.28004.9b


zbMATH Keywords

support vector machinesGaussian kernelparameter settinglearning rankingsMeta-learning


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)


Related Items (8)

Learning dynamic algorithm portfolios ⋮ Pairwise meta-rules for better meta-learning-based algorithm ranking ⋮ FSPL: a meta-learning approach for a filter and embedded feature selection pipeline ⋮ A meta-learning approach to the regularized learning -- case study: blood glucose prediction ⋮ Efficient benchmarking of algorithm configurators via model-based surrogates ⋮ Unnamed Item ⋮ Data complexity meta-features for regression problems ⋮ KBER: A kernel bandwidth estimate using the Ricci curvature


Uses Software

  • R
  • SVMTorch



This page was built for publication: A meta-learning method to select the kernel width in support vector regression

Retrieved from "https://portal.mardi4nfdi.de/w/index.php?title=Publication:703049&oldid=12617909"
Tools
What links here
Related changes
Special pages
Printable version
Permanent link
Page information
MaRDI portal item
This page was last edited on 30 January 2024, at 09:57.
Privacy policy
About MaRDI portal
Disclaimers
Imprint
Powered by MediaWiki