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A tutorial on multilabel learning
E Gibaja, S Ventura - ACM Computing Surveys (CSUR), 2015 - dl.acm.org
Multilabel learning has become a relevant learning paradigm in the past years due to the
increasing number of fields where it can be applied and also to the emerging number of …
increasing number of fields where it can be applied and also to the emerging number of …
Multi‐label learning: a review of the state of the art and ongoing research
E Gibaja, S Ventura - Wiley Interdisciplinary Reviews: Data …, 2014 - Wiley Online Library
Multi‐label learning is quite a recent supervised learning paradigm. Owing to its capabilities
to improve performance in problems where a pattern may have more than one associated …
to improve performance in problems where a pattern may have more than one associated …
A survey of hierarchical classification across different application domains
CN Silla, AA Freitas - Data mining and knowledge discovery, 2011 - Springer
In this survey we discuss the task of hierarchical classification. The literature about this field
is scattered across very different application domains and for that reason research in one …
is scattered across very different application domains and for that reason research in one …
Multilabel neural networks with applications to functional genomics and text categorization
In multilabel learning, each instance in the training set is associated with a set of labels and
the task is to output a label set whose size is unknown a priori for each unseen instance. In …
the task is to output a label set whose size is unknown a priori for each unseen instance. In …
Coherent hierarchical multi-label classification networks
E Giunchiglia, T Lukasiewicz - Advances in neural …, 2020 - proceedings.neurips.cc
Hierarchical multi-label classification (HMC) is a challenging classification task extending
standard multi-label classification problems by imposing a hierarchy constraint on the …
standard multi-label classification problems by imposing a hierarchy constraint on the …
Decision trees for hierarchical multi-label classification
C Vens, J Struyf, L Schietgat, S Džeroski, H Blockeel - Machine learning, 2008 - Springer
Hierarchical multi-label classification (HMC) is a variant of classification where instances
may belong to multiple classes at the same time and these classes are organized in a …
may belong to multiple classes at the same time and these classes are organized in a …
An intelligent intrusion detection system (IDS) for anomaly and misuse detection in computer networks
In this paper, we propose a novel Intrusion Detection System (IDS) architecture utilizing both
anomaly and misuse detection approaches. This hybrid Intrusion Detection System …
anomaly and misuse detection approaches. This hybrid Intrusion Detection System …
Tree ensembles for predicting structured outputs
D Kocev, C Vens, J Struyf, S Džeroski - Pattern Recognition, 2013 - Elsevier
In this paper, we address the task of learning models for predicting structured outputs. We
consider both global and local predictions of structured outputs, the former based on a …
consider both global and local predictions of structured outputs, the former based on a …
[PDF][PDF] Multi-label classification on tree-and dag-structured hierarchies
W Bi, JT Kwok - Proceedings of the 28th International Conference …, 2011 - cse.hkust.edu.hk
Many real-world applications involve multilabel classification, in which the labels are
organized in the form of a tree or directed acyclic graph (DAG). However, current research …
organized in the form of a tree or directed acyclic graph (DAG). However, current research …
Predicting gene function using hierarchical multi-label decision tree ensembles
L Schietgat, C Vens, J Struyf, H Blockeel, D Kocev… - BMC …, 2010 - Springer
Background S. cerevisiae, A. thaliana and M. musculus are well-studied organisms in
biology and the sequencing of their genomes was completed many years ago. It is still a …
biology and the sequencing of their genomes was completed many years ago. It is still a …