Multi-label classification and extracting predicted class hierarchies

DOI10.1016/j.patcog.2010.09.010zbMath1209.68442OpenAlexW1991661982MaRDI QIDQ622024

Florian Brucker, Fernando Benites, Elena Sapozhnikova

Publication date: 31 January 2011

Published in: Pattern Recognition (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.patcog.2010.09.010

zbMATH Keywords

text miningmulti-label classificationadaptive resonance theory (ART)hierarchy extraction

Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)

Related Items (2)

Multi-label core vector machine with a zero label ⋮ Extracting hierarchies from data clusters for better classification

Uses Software

• RCV1
• AdaBoost.MH
• BoosTexter
• Bow
• ML-KNN
• Fuzzy ARTMAP

Cites Work

• Predictive neural networks for gene expression data analysis
• ML-KNN: A lazy learning approach to multi-label learning
• Decision trees for hierarchical multi-label classification
• Some MAX SNP-hard results concerning unordered labeled trees
• A decision-theoretic generalization of on-line learning and an application to boosting
• BoosTexter: A boosting-based system for text categorization
• A constrained edit distance between unordered labeled trees
• A Conceptual Graph Based Approach to Ontology Similarity Measure
• A massively parallel architecture for a self-organizing neural pattern recognition machine
• The Tree-to-Tree Correction Problem
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