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International journal of approximate reasoning, ISSN 0888-613X, 2016, Volume 68, pp. 179 - 193
Multi-label classification assigns more than one label for each instance; when the labels are ordered in a predefined structure, the task is called... 
Multi-label classification | Hierarchical classification | Chain classifiers | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | TOOL | Analysis | Algorithms | Trees | Hierarchies | Tasks | Approximation | Classification | Labels | Explosions | Dealing
Journal Article
Computer applications in engineering education, ISSN 1061-3773, 2016, Volume 24, Issue 4, pp. 651 - 660
Journal Article
Journal of Machine Learning Research, ISSN 1532-4435, 07/2011, Volume 12, pp. 2411 - 2414
Journal Article
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2014, Volume 8536, pp. 100 - 108
Conference Proceeding
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), ISSN 0302-9743, 2015, Volume 9043, pp. 557 - 564
Conference Proceeding
Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science), ISSN 0302-9743, 2015, Volume 8983, pp. 19 - 37
Conference Proceeding
Journal Article
International Journal of Computational Intelligence Systems, ISSN 1875-6891, 12/2015, Volume 8, Issue sup2, pp. 3 - 15
Feature selection can remove non-important features from the data and promote better classifiers. This task, when applied to multi-label data where each... 
information gain | label construction for feature selection | survey | multi-label ReliefF | machine learning | data mining | COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS | RELIEFF | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Journal Article
Pattern recognition, ISSN 0031-3203, 2017, Volume 67, pp. 410 - 423
•We granulate the label space into information granules to exploit label dependency.•We present a multi-label maximal correlation minimal redundancy... 
Multi-label learning | Feature selection | Granular computing | Mutual information | TRANSFORMATION | LUNG-CANCER | SETS | CLASSIFICATION | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE | ENGINEERING, ELECTRICAL & ELECTRONIC | Computer science | Embedded systems | Algorithms | Educational evaluation | Machine learning
Journal Article
Proceedings of the 33rd international ACM SIGIR conference on research and development in information retrieval, 07/2010, pp. 315 - 322
Effective learning in multi-label classification (MLC) requires an appropriate level of abstraction for representing the relationship between each instance and... 
comparative evaluation | model design | multi-label classification | learning to rank | Comparative evaluation | Learning to rank | Multi-label classification | Model design
Conference Proceeding
Pattern recognition, ISSN 0031-3203, 2017, Volume 66, pp. 342 - 352
Journal Article
Information Processing and Management, ISSN 0306-4573, 05/2018, Volume 54, Issue 3, pp. 359 - 369
•Evaluation measures have been used arbitrarily in multilabel classification experiments, without an objective analysis of correlation or bias... 
Multi-label classification | Evaluation measures | FEATURE-SELECTION | TRANSFORMATION | COMPUTER SCIENCE, INFORMATION SYSTEMS | INFORMATION SCIENCE & LIBRARY SCIENCE
Journal Article
Machine Learning, ISSN 0885-6125, 4/2018, Volume 107, Issue 4, pp. 703 - 725
Journal Article
Journal Article