221 search results - page 31 / 45 » Learning from Labeled and Unlabeled Data Using Random Walks |
ICPR
2002
IEEE
14 years 9 months ago
2002
IEEE
Learning Bayesian Belief Networks (BBN) from corpora and incorporating the extracted inferring knowledge with a Support Vector Machines (SVM) classifier has been applied to charac...
IJSI
2008
13 years 7 months ago
2008
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
KDD
2010
ACM
13 years 10 months ago
2010
ACM
In plenty of scenarios, data can be represented as vectors mathematically abstracted as points in a Euclidean space. Because a great number of machine learning and data mining app...
AAAI
2008
13 years 10 months ago
2008
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
PRIB
2010
Springer
13 years 6 months ago
2010
Springer
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...