Open AccessLearning From Positive and Unlabeled Examples
Author(s) -
Fabien Letouzey,
François Denis,
Rémi Gilleron
Publication year - 2000
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-41237-9
DOI - 10.1007/3-540-40992-0_6
Subject(s) - computer science , class (philosophy) , set (abstract data type) , artificial intelligence , decision tree , machine learning , statistical model , algorithm , tree (set theory) , time complexity , mathematics , combinatorics , programming language
In many machine learning settings, examples of one class(called positive class) are easily available. Also, unlabeled data are abundant.
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