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» Closed Sets for Labeled Data
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WWW
2009
ACM
14 years 11 months ago
Large scale multi-label classification via metalabeler
The explosion of online content has made the management of such content non-trivial. Web-related tasks such as web page categorization, news filtering, query categorization, tag r...
Lei Tang, Suju Rajan, Vijay K. Narayanan
IJCAI
2003
14 years 5 days ago
Semi-Supervised Learning with Explicit Misclassification Modeling
This paper investigates a new approach for training discriminant classifiers when only a small set of labeled data is available together with a large set of unlabeled data. This a...
Massih-Reza Amini, Patrick Gallinari
PODS
2005
ACM
85views Database» more  PODS 2005»
14 years 11 months ago
Relative risk and odds ratio: a data mining perspective
We are often interested to test whether a given cause has a given effect. If we cannot specify the nature of the factors involved, such tests are called model-free studies. There ...
Haiquan Li, Jinyan Li, Limsoon Wong, Mengling Feng...
ACL
2008
14 years 7 days ago
Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields
This paper presents a semi-supervised training method for linear-chain conditional random fields that makes use of labeled features rather than labeled instances. This is accompli...
Gideon S. Mann, Andrew McCallum
JIFS
2008
155views more  JIFS 2008»
13 years 10 months ago
Improving supervised learning performance by using fuzzy clustering method to select training data
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Andrey G...