Results 31 to 40 of about 881,675 (221)
Multi-label Classification with Meta-Labels [PDF]
2014 IEEE International Conference on Data Mining, 2014 The area of multi-label classification has rapidly developed in recent years. It has become widely known that the baseline binary relevance approach can easily be outperformed by methods which learn labels together. A number of methods have grown around the label power set approach, which models label combinations together as class values in a multi ...
Bifet, Albert, Read, Jesse
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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
doaj +1 more source
Semantic Diversity Learning for Zero-Shot Multi-label Classification [PDF]
IEEE International Conference on Computer Vision, 2021 Training a neural network model for recognizing multiple labels associated with an image, including identifying unseen labels, is challenging, especially for images that portray numerous semantically diverse labels.
Avi Ben-Cohen +4 more
semanticscholar +1 more source
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
doaj +1 more source
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
Holmes, Geoffrey +2 more
core +2 more sources
Multi-Label Retinal Disease Classification Using Transformers
IEEE Journal of Biomedical and Health Informatics, 2023 Early detection of retinal diseases is one of the most important means of preventing partial or permanent blindness in patients. In this research, a novel multi-label classification system is proposed for the detection of multiple retinal diseases, using fundus images collected from a variety of sources. First, a new multi-label retinal disease dataset,
Manuel Alejandro Rodríguez +2 more
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On Missing Labels, Long-tails and Propensities in Extreme Multi-label Classification [PDF]
Knowledge Discovery and Data Mining, 2022 The propensity model introduced by Jain et al has become a standard approach for dealing with missing and long-tail labels in extreme multi-label classification (XMLC).
Erik Schultheis +3 more
semanticscholar +1 more source
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
doaj +1 more source
Ensemble methods for multi-label classification [PDF]
Expert Systems with Applications, 2014 Ensemble methods have been shown to be an effective tool for solving multi-label classification tasks. In the RAndom k-labELsets (RAKEL) algorithm, each member of the ensemble is associated with a small randomly-selected subset of k labels. Then, a single label classifier is trained according to each combination of elements in the subset. In this paper
Rokach, Lior, Schclar, Alon, Itach, Ehud
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Evaluating Extreme Hierarchical Multi-label Classification
Annual Meeting of the Association for Computational Linguistics, 2022 Several natural language processing (NLP) tasks are defined as a classification problem in its most complex form: Multi-label Hierarchical Extreme classification, in which items may be associated with multiple classes from a set of thousands of possible ...
Enrique Amigó, A. Delgado
semanticscholar +1 more source