Bonsai: diverse and shallow trees for extreme multi-label classification

DOI10.1007/s10994-020-05888-2OpenAlexW3080802002MaRDI QIDQ2217402

Sujay Khandagale, Han Xiao, Rohit Babbar

Publication date: 29 December 2020

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

Full work available at URL: https://arxiv.org/abs/1904.08249

zbMATH Keywords

extreme multi-label classificationlarge label spacelarge-scale multi-label classification

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Related Items (2)

Speeding-up one-versus-all training for extreme classification via mean-separating initialization ⋮ Large scale multi-label learning using Gaussian processes

Uses Software

• LIBLINEAR
• word2vec
• ImageNet
• GitHub
• FastXML
• AnnexML
• DiSMEC
• WSABIE
• AlexNet

Cites Work

• Decision trees for hierarchical multi-label classification
• Data scarcity, robustness and extreme multi-label classification
• Least squares quantization in PCM
• Multilabel Classification with Principal Label Space Transformation
• Machine Learning: ECML 2004
• Unnamed Item
• Unnamed Item

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