Hierarchical Multi-label Classification
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Benchmarks
RCV1-v2
EURLEX57K
WOS
Cellcycle Funcat
Cellcycle GO
Derisi Funcat
Derisi GO
Eisen Funcat
Eisen GO
Expr Funcat
Expr GO
Gasch1 Funcat
Gasch1 GO
Gasch2 Funcat
Gasch2 GO
Seq Funcat
Seq GO
Spo Funcat
Spo GO
Most implemented
Clinically-Inspired Hierarchical Multi-Label Classification of Chest X-rays with a Penalty-Based Loss Function
Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery
Hierarchy-aware Biased Bound Margin Loss Function for Hierarchical Text Classification
Error Detection and Constraint Recovery in Hierarchical Multi-Label Classification without Prior Knowledge
Papers
Taxlifier: Leveraging Disease Taxonomy for Enhanced Multi-Label Classification in Chest Radiography
Accurate and efficient classification of thoracic diseases in chest X-ray (CXR) images is crucial for timely diagnosis and treatment. However, the presence of multiple pathologies with overlapping visual characteristics …
Hierarchical Multi-label ClassificationEvaluation Sovereignty in Metadata-Driven Classification: A Multi-Track Framework for Weakly Supervised Information Systems
Evaluation in machine learning is typically treated as a neutral measurement process. However, in operational information systems, evaluation outcomes are often conditioned by the processes used to generate labels. This …
Hierarchical Multi-label ClassificationMAPLE: Multi-Path Adaptive Propagation with Level-Aware Embeddings for Hierarchical Multi-Label Image Classification
Hierarchical multi-label classification (HMLC) is essential for modeling structured label dependencies in remote sensing. Yet existing approaches struggle in multi-path settings, where images may activate multiple taxono…
Hierarchical Multi-label ClassificationMulti-Label Image ClassificationHELM: Hierarchical and Explicit Label Modeling with Graph Learning for Multi-Label Image Classification
Hierarchical multi-label classification (HMLC) is essential for modeling complex label dependencies in remote sensing. Existing methods, however, struggle with multi-path hierarchies where instances belong to multiple br…
Hierarchical Multi-label ClassificationMulti-Label Image ClassificationGraph LearningAn Analysis of Multi-Task Architectures for the Hierarchic Multi-Label Problem of Vehicle Model and Make Classification
Most information in our world is organized hierarchically; however, many Deep Learning approaches do not leverage this semantically rich structure. Research suggests that human learning benefits from exploiting the hiera…
Hierarchical Multi-label ClassificationMulti-Task LearningImproving Detection of Rare Nodes in Hierarchical Multi-Label Learning
In hierarchical multi-label classification, a persistent challenge is enabling model predictions to reach deeper levels of the hierarchy for more detailed or fine-grained classifications. This difficulty partly arises fr…
Hierarchical Multi-label ClassificationMulti-Label Learning