Results 11 to 20 of about 728,673 (266)
Annals of Mathematics and Artificial Intelligence, 2008 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fietzke, A. +1 more
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Multi-Label Classification with Label Clusters
Knowledge and Information Systems, 2023 Abstract Multi-Label Classification is the task of simultaneously predicting a set of labels for an instance. Typically, two approaches are used: global, which trains a single classifier to deal with all classes at once, and local, which divides the problem into many binary problems.
Elaine Cecília Gatto +2 more
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The role of exercise and diet in maintaining bone health
Journal of Physical Fitness and Sports Medicine, 2012 Prevention is the most important measure against osteoporosis, since bone mass, once it is lost, cannot be recovered. Bone mass, in both men and women, reaches a maximum level in the 20s to 30s age range, and maintains this level or slightly increases ...
Yoshiko Ishimi, Kaoru Yanaka
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Point labeling with sliding labels
Computational Geometry, 1999 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
van Kreveld, M.J. +2 more
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LABEL PROPAGATION FOR LEARNING WITH LABEL PROPORTIONS [PDF]
2018 IEEE 28th International Workshop on Machine Learning for Signal Processing (MLSP), 2018 Accepted to MLSP ...
Rafael Poyiadzi +2 more
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Multi-label Learning with Label Enhancement [PDF]
2018 IEEE International Conference on Data Mining (ICDM), 2018 The task of multi-label learning is to predict a set of relevant labels for the unseen instance. Traditional multi-label learning algorithms treat each class label as a logical indicator of whether the corresponding label is relevant or irrelevant to the instance, i.e., +1 represents relevant to the instance and -1 represents irrelevant to the instance.
Ruifeng Shao +2 more
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Translational Oncology, 2019 Off-target activities of drug candidates observed during in vitro pharmacological profiling frequently do not translate to adverse events (AEs) in human. This could be because off-target activities do not have functional consequences, are not observed at
Hamid R. Amouzadeh +6 more
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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 ...
Jesse Read, Antti Puurula, Albert Bifet
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Estimating labels from label proportions [PDF]
Proceedings of the 25th international conference on Machine learning - ICML '08, 2008 Consider the following problem: given sets of unlabeled observations, each set with known label proportions, predict the labels of another set of observations, also with known label proportions. This problem appears in areas like e-commerce, spam filtering and improper content detection.
Novi Quadrianto +3 more
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Labeling of Polysaccharides with Biotin and Fluorescent Dyes
Polysaccharides, 2023 Examples of labeling polysaccharides at hydroxyl groups are described in this paper, which are especially in demand for molecules with a blocked reducing end.
Alexander Tuzikov +8 more
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