Learning with positive and unlabeled examples using weighted logistic regression
Published 21 August 2003Open access
Wee Sun Lee, Bing Liu
Citations334
SJR quartileQ4
SJR score0.11
SNIP0.06
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TL;DR
A performance measure that can be estimated from positive and unlabeled examples for evaluating retrieval performance, which is proportional to the product of precision and recall, can be used with a validation set to select regularization parameters for logistic regression.
Abstract
The problem of learning with positive and unlabeled examples arises frequently in retrieval applications.
Keywords
Computer Science
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