Multi-Label Classification with Meta-Label-Specific Features and Q-Learning [PDF]
Control and Optimization in Applied Mathematics, 2021 Classification is a crucial process in data mining, data science, machine learning, and the applications of natural language processing. Classification methods distinguish the correlation between the data and the output classes.
Seyed Hossein Seyed Ebrahimi +2 more
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Asymmetric Loss For Multi-Label Classification [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 Accepted to ICCV ...
Tal Ridnik +6 more
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Neural Tensor Network for Multi- Label Classification
IEEE Access, 2019 The difference of multi-label classification from traditional classification is that an instance may associate a set of labels simultaneously. In recent study, some scholars have proposed that the information which derives from the query instance's ...
Wenxing Hong +3 more
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A hierarchical multi-label classification ant colony algorithm for protein function prediction [PDF]
, 2010 This paper proposes a novel ant colony optimisation (ACO) algorithm tailored for the hierarchical multi-label classification problem of protein function prediction.
Otero, Fernando E.B. +5 more
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Multi-label classification using ensembles of pruned sets [PDF]
, 2008 This paper presents a Pruned Sets method (PS) for multi-label classification. It is centred on the concept of treating sets of labels as single labels. This allows the classification process to inherently take into account correlations between labels. By
Pfahringer, Bernhard +5 more
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Discriminative Adaptive Sets for Multi-Label Classification
IEEE Access, 2020 Multi-label classification aims to associate multiple labels to a given data/object instance to better describe them. Multi-label data sets are common in a lot of emerging application areas like: Text/Multimedia classification, Bio-Informatics, Medical ...
Muhammad Usman Ghani +2 more
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A New Ant Colony Algorithm for Multi-Label Classification with Applications in Bioinformatics [PDF]
, 2006 The conventional classification task of data mining can be called single-label classification, since there is a single class attribute to be predicted.
Chan, Allen +3 more
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HMATC: Hierarchical multi-label Arabic text classification model using machine learning
Egyptian Informatics Journal, 2021 Multi-label classification assigns multiple labels to each document concurrently. Many real-world classification problems tend to employ high-dimensional label spaces, which can be naturally structured in a hierarchy.
Nawal Aljedani +2 more
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Comparing Multi-Label Classification Methods for Provisional Biopharmaceutics Class Prediction. [PDF]
, 2014 The biopharmaceutical classification system (BCS) is now well established and utilized for the development and biowaivers of immediate oral dosage forms. The prediction of BCS class can be carried out using multilabel classification.
Taravat Ghafourian +8 more
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A multi-label classification approach via hierarchical multi-label classification
, 2022 Abstract Multi-label classification (MLC) is a very explored field in recent years. The most common approaches that deal with MLC problems are classified into two groups: (i) problem transformation which aims to adapt the multi-label data, making the use of traditional binary or multiclass classification algorithms feasible, and (ii) algorithm ...
Mauri Ferrandin, Ricardo Cerri
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