Classifier chains

Classifier chains is a machine learning method for problem transformation in multi-label classification. It combines the computational efficiency of… (More)
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Topic mentions per year

Topic mentions per year

2006-2017
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Papers overview

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2015
2015
Multi-label classification is a challenging and appealing supervised learning problem where a subset of labels, rather than a… (More)
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2015
2015
In multi-label classification, labels often have correlations with each other. Exploiting label correlations can improve the… (More)
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2013
2013
In multi-label learning, the relationship among labels is well accepted to be important, and various methods have been proposed… (More)
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2013
2013
A plethora of emerging Big Data applications require processing and analyzing streams of data to extract valuable information in… (More)
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2013
2013
First proposed in 2009, the classifier chains model (CC) has become one of the most influential algorithms for multi-label… (More)
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2013
2013
Multi-label classification (MLC) is the supervised learning problem where an instance may be associated with multiple labels… (More)
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Highly Cited
2010
Highly Cited
2010
In the realm of multilabel classification (MLC), it has become an opinio communis that optimal predictive performance can only be… (More)
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2010
2010
In the real world, images always have several visual objects instead of only one, which makes it difficult for conventional… (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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2007
2007
Networks of classifiers are capturing the attention of system and algorithmic researchers because they offer improved accuracy… (More)
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