Multi-label classification

Known as: Algorithm adaptation methods, Multi-label, RAKEL 
In machine learning, multi-label classification and the strongly related problem of multi-output classification are variants of the classification… (More)
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Topic mentions per year

Topic mentions per year

1972-2018
010020030019722018

Papers overview

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Highly Cited
2011
Highly Cited
2011
In this paper, we tackle the challenges of multilabel classification by developing a general conditional dependency network model… (More)
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Highly Cited
2009
Highly Cited
2009
The widely known binary relevance method for multi-label classification, which considers each label as an independent binary… (More)
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Highly Cited
2009
Highly Cited
2009
The explosion of online content has made the management of such content non-trivial. Web-related tasks such as web page… (More)
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Highly Cited
2008
Highly Cited
2008
In this paper, the automated detection of emotion in music is modeled as a multilabel classification task, where a piece of music… (More)
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Highly Cited
2008
Highly Cited
2008
Hierarchical multi-label classification (HMC) is a variant of classification where instances may belong to multiple classes at… (More)
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Highly Cited
2008
Highly Cited
2008
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set… (More)
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Highly Cited
2008
Highly Cited
2008
This paper presents a pruned sets method (PS) for multi-label classification. It is centred on the concept of treating sets of… (More)
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Highly Cited
2008
Highly Cited
2008
Multi-label problems arise in various domains such as multi-topic document categorization and protein function prediction. One… (More)
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Highly Cited
2005
Highly Cited
2005
Common approaches to multi-label classification learn independent classifiers for each category, and employ ranking or… (More)
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Highly Cited
2001
Highly Cited
2001
This article presents a Support Vector Machine (SVM) like learning system to handle multi-label problems. Such problems are… (More)
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