Global multi-output decision trees for interaction prediction

DOI10.1007/s10994-018-5700-xzbMath1473.68160OpenAlexW2800240915MaRDI QIDQ1631785

Celine Vens, Pierre Geurts, Konstantinos Pliakos

Publication date: 7 December 2018

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

Full work available at URL: https://doi.org/10.1007/s10994-018-5700-x

zbMATH Keywords

decision treeheterogeneous networksinteraction datamulti-output learning

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• MULAN
• ML-KNN

Cites Work

• Introduction to the special issue on learning from multi-label data
• On label dependence and loss minimization in multi-label classification
• ML-KNN: A lazy learning approach to multi-label learning
• Decision trees for hierarchical multi-label classification
• Network regression with predictive clustering trees
• Machine learning: Trends, perspectives, and prospects
• Extremely randomized trees
• Random forests
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