Two-View Transductive Support Vector Machines

8 years 4 months ago
Two-View Transductive Support Vector Machines
Obtaining high-quality and up-to-date labeled data can be difficult in many real-world machine learning applications, especially for Internet classification tasks like review spam detection, which changes at a very brisk pace. For some problems, there may exist multiple perspectives, so called views, of each data sample. For example, in text classification, the typical view contains a large number of raw content features such as term frequency, while a second view may contain a small but highly-informative number of domain specific features. We thus propose a novel two-view transductive SVM that takes advantage of both the abundant amount of unlabeled data and their multiple representations to improve the performance of classifiers. The idea is fairly simple: train a classifier on each of the two views of both labeled and unlabeled data, and impose a global constraint that each classifier assigns the same class label to each labeled and unlabeled data. We applied our two-view transduc...
Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2010
Where SDM
Authors Guangxia Li, Steven C. H. Hoi, Kuiyu Chang
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