Metalearning and algorithm selection: progress, state of the art and introduction to the 2018 special issue

DOI10.1007/s10994-017-5692-yzbMath1386.68125OpenAlexW2780926888MaRDI QIDQ1707460

No author found.

Publication date: 3 April 2018

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

Full work available at URL: https://doi.org/10.1007/s10994-017-5692-y

zbMATH Keywords

metalearninghyperparameter optimizationalgorithm selection and configurationautomated ensemble construction

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Collections of articles of miscellaneous specific interest (00B15) Proceedings, conferences, collections, etc. pertaining to computer science (68-06)

Related Items (2)

AutonoML: Towards an Integrated Framework for Autonomous Machine Learning ⋮ A Comparison of Robust Model Choice Criteria Within a Metalearning Study

Uses Software

• irace
• Scikit
• rapidminer
• TPOT
• Auto-WEKA
• SMAC
• auto-sklearn

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Algorithm runtime prediction: methods \& evaluation
• Empirical hardness models
• Metalearning
• ParamILS: An Automatic Algorithm Configuration Framework
• Random forests

This page was built for publication: Metalearning and algorithm selection: progress, state of the art and introduction to the 2018 special issue