Classifier chains for multi-label classification
Citations
2,495 citations
Cites background from "Classifier chains for multi-label c..."
...In Classifier Chains [72], [73], binary assignment is represented by 0 and 1....
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...67 · |D|) [72] or with replacement (|D(r)| = |D|) [73]....
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...The basic idea of this algorithm is to transform the multilabel learning problem into a chain of binary classification problems, where subsequent binary classifiers in the chain is built upon the predictions of preceding ones [72], [73]....
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2,227 citations
Cites methods from "Classifier chains for multi-label c..."
...The F measure was originally introduced for measuring classification performance in information retrieval processes (van Rijsbergen, 1979) and has been used frequently in assessing the performance of binary or multilabel classifiers (Lan et al., 2012; Read et al., 2011)....
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1,073 citations
Cites methods from "Classifier chains for multi-label c..."
...As binary classification algorithm, we have employed logistic regression and SVM with RBF kernel provided in LIBSVM [19], for the cases of weighted Euclidean and weighted loss-based decodings respectively....
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...We adapted the measure NDCG [19] (Normalized Discounted Cumulative Gain) to form our metatarget....
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...In order to construct a more informative gene network we performed the integration by adding two more functional gene networks (FI and HumanNet) taken from the literature [18,19], thus obtaining a final integration of 10 biomolecular networks (Table 1)....
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933 citations
711 citations
Cites methods from "Classifier chains for multi-label c..."
...Each base classifier makes a multi-label prediction and then these predictions are combined by using some voting scheme (e.g., majority or probability distribution voting)....
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...This method proved to be particularly competitive in terms of efficiency....
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...All rights reserved....
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References
20,196 citations
"Classifier chains for multi-label c..." refers methods in this paper
...We evaluate all algorithms under a WEKA-based [17] framework running under Java JDK 1....
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19,603 citations
"Classifier chains for multi-label c..." refers methods in this paper
...We evaluate all algorithms using our open-source WEKA-based (Hall et al. 2009) software,2 which also provides a wrapper around the MULAN software3 that contains additional methods....
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...Improving these algorithms, including threshold selection, was a focus of the work in Kiritchenko (2005). AdaBoost-based methods have mainly been used in bioinformatics applications (where boosting and decision trees are particularly popular (Kiritchenko 2005))....
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...We evaluate all algorithms under a WEKA-based [17] framework running under Java JDK 1.6 with the following settings....
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17,177 citations
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16,118 citations
10,306 citations
"Classifier chains for multi-label c..." refers methods in this paper
...We apply the Nemenyi test (Demšar 2006) to indicate statistical significance....
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