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ECAI
2006
Springer
13 years 8 months ago
A Unified Model for Multilabel Classification and Ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operate...
Klaus Brinker, Johannes Fürnkranz, Eyke H&uum...
KDD
2007
ACM
190views Data Mining» more  KDD 2007»
14 years 4 months ago
Model-shared subspace boosting for multi-label classification
Typical approaches to multi-label classification problem require learning an independent classifier for every label from all the examples and features. This can become a computati...
Rong Yan, Jelena Tesic, John R. Smith
PRIB
2010
Springer
192views Bioinformatics» more  PRIB 2010»
13 years 2 months ago
Structured Output Prediction of Anti-cancer Drug Activity
We present a structured output prediction approach for classifying potential anti-cancer drugs. Our QSAR model takes as input a description of a molecule and predicts the activity...
Hongyu Su, Markus Heinonen, Juho Rousu
ML
2008
ACM
134views Machine Learning» more  ML 2008»
13 years 4 months ago
Multilabel classification via calibrated label ranking
Label ranking studies the problem of learning a mapping from instances to rankings over a predefined set of labels. Hitherto existing approaches to label ranking implicitly operat...
Johannes Fürnkranz, Eyke Hüllermeier, En...
KDD
2009
ACM
156views Data Mining» more  KDD 2009»
14 years 5 months ago
Effective multi-label active learning for text classification
Labeling text data is quite time-consuming but essential for automatic text classification. Especially, manually creating multiple labels for each document may become impractical ...
Bishan Yang, Jian-Tao Sun, Tengjiao Wang, Zheng Ch...