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- PU_learning abstract "In machine learning, PU learning is a collection of semisupervised techniques for training binary classifiers on positive and unlabeled examples only.In PU learning, two sets of samples are assumed to be available for training: the positive set and a mixed set , which is assumed to contain both positive and negative samples, but without these being labeled as such. This contrasts with other forms of semisupervised learning, where it is assumed that a labeled set containing examples of both classes is available. A variety of techniques exist to adapt supervised classifiers to the PU learning setting. PU learning successfully been applied to text classification and Bioinformatics tasks.".
- PU_learning wikiPageID "33193691".
- PU_learning wikiPageRevisionID "597938826".
- PU_learning hasPhotoCollection PU_learning.
- PU_learning subject Category:Machine_learning.
- PU_learning comment "In machine learning, PU learning is a collection of semisupervised techniques for training binary classifiers on positive and unlabeled examples only.In PU learning, two sets of samples are assumed to be available for training: the positive set and a mixed set , which is assumed to contain both positive and negative samples, but without these being labeled as such.".
- PU_learning label "PU learning".
- PU_learning sameAs m.0h637f8.
- PU_learning sameAs Q7121113.
- PU_learning sameAs Q7121113.
- PU_learning wasDerivedFrom PU_learning?oldid=597938826.
- PU_learning isPrimaryTopicOf PU_learning.