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Classifier chains

Classifier chains is a machine learning method for problem transformation in multi-label classification. It combines the computational efficiency of… Expand
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Papers overview

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2015
2015
Multi-output inference tasks, such as multi-label classification, have become increasingly important in recent years. A popular… Expand
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Highly Cited
2014
Highly Cited
2014
Multi-dimensional classification (MDC) is the supervised learning problem where an instance is associated with multiple classes… Expand
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Highly Cited
2014
Highly Cited
2014
We introduce a novel method for chaining Bayesian classifiers.We provide a detailed analysis of the proposed method.We perform an… Expand
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Highly Cited
2013
Highly Cited
2013
First proposed in 2009, the classifier chains model (CC) has become one of the most influential algorithms for multi-label… Expand
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2013
2013
Multi-label classification, in opposite to conventional classification, assumes that each data instance may be associated with… Expand
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Highly Cited
2011
Highly Cited
2011
The widely known binary relevance method for multi-label classification, which considers each label as an independent binary… Expand
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Highly Cited
2011
Highly Cited
2011
In multidimensional classification the goal is to assign an instance to a set of different classes. This task is normally… Expand
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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… Expand
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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… Expand
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2007
2007
Networks of classifiers are capturing the attention of system and algorithmic researchers because they offer improved accuracy… Expand
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