On the effectiveness of heuristics for learning nested dichotomies: an empirical analysis

DOI10.1007/s10994-018-5733-1zbMath1475.68285OpenAlexW2809939257WikidataQ129617423 ScholiaQ129617423MaRDI QIDQ1631807

Vitalik Melnikov, Eyke Hüllermeier

Publication date: 7 December 2018

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

Full work available at URL: https://doi.org/10.1007/s10994-018-5733-1

zbMATH Keywords

decomposition methodmulti-class classificationnested dichotomies

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20)

Related Items (1)

Efficient set-valued prediction in multi-class classification

Uses Software

• Scikit
• OpenML
• Auto-WEKA
• auto-sklearn

Cites Work

• Numbering binary trees with labeled terminal vertices
• The generation of random, binary unordered trees
• 10.1162/153244302320884605
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