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
core +1 more source
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 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
core +1 more source
A lexicographic multi-objective genetic algorithm for multi-label correlation-based feature selection [PDF]
, 2015 This paper proposes a new Lexicographic multi-objective Genetic Algorithm for Multi-Label Correlation-based Feature Selection (LexGA-ML-CFS), which is an extension of the previous single-objective Genetic Algorithm for Multi-label Correlation-based ...
Suwimol Jungjit +3 more
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Simpler is better: a novel genetic algorithm to induce compact multi-label chain classifiers [PDF]
, 2015 Multi-label classification (MLC) is the task of assigning multiple class labels to an object based on the features that describe the object. One of the most effective MLC methods is known as Classifier Chains (CC).
Plastino, Alexandre +5 more
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Classifier Chains for Multi-Label Classification with Incomplete Labels [PDF]
Many methods have been explored in the literature of multi-label learning, ranging from simple problem transformation to more complex method that capture correlation among labels.
Almuallim, Jafer
core +6 more sources
Collective Multi-Label Classification [PDF]
, 2005 Common approaches to multi-label classification learn independent classifiers for each category, and employ ranking or thresholding schemes for classification. Because they do not exploit dependen-cies between labels, such techniques are only well-suited
Nadia Ghamrawi, Andrew Mccallum
core +4 more sources
Adaptive Disentangled Representation Learning for Incomplete Multi-View Multi-Label Classification
CoRRMulti-view multi-label learning frequently suffers from simultaneous feature absence and incomplete annotations, due to challenges in data acquisition and cost-intensive supervision. To tackle the complex yet highly practical problem while overcoming the existing limitations of feature recovery, representation disentanglement, and label semantics ...
Quanjiang Li +4 more
openaire +3 more sources
A new genetic algorithm for multi-label correlation-based feature selection. [PDF]
, 2015 This paper proposes a new Genetic Algorithm for Multi-Label Correlation-Based Feature Selection (GA-ML-CFS). This GA performs a global search in the space of candidate feature subset, in order to select a high-quality feature subset is used by a multi ...
Jungjit, Suwimol, Freitas, Alex A.
core +1 more source