Experiment databases

DOI10.1007/S10994-011-5277-0zbMath1238.68134OpenAlexW2153380237WikidataQ55967226 ScholiaQ55967226MaRDI QIDQ420934

Bernhard Pfahringer, Hendrik Blockeel, Geoffrey Holmes, Joaquin Vanschoren

Publication date: 23 May 2012

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

Full work available at URL: https://doi.org/10.1007/s10994-011-5277-0

zbMATH Keywords

experimental methodologymachine learningdatabasesmeta-learning

Mathematics Subject Classification ID

Database theory (68P15) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (3)

ASlib: a benchmark library for algorithm selection ⋮ Sparse multivariate regression with missing values and its application to the prediction of material properties ⋮ \texttt{OpenML}: an \texttt{R} package to connect to the machine learning platform OpenML

Uses Software

• UCI-ml
• WEKA

Cites Work

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• Multiple comparisons in induction algorithms
• Very simple classification rules perform well on most commonly used datasets
• Classifier technology and the illusion of progress
• 10.1162/153244304322972694
• Metalearning
• Data Mining Research: Current Status and Future Opportunities
• The effect of instance-space partition on significance

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