Adaptively Weighted Large Margin Classifiers.

TitleAdaptively Weighted Large Margin Classifiers.
Publication TypeJournal Article
Year of Publication2013
AuthorsWu, Yichao, and Yufeng Liu
JournalJ Comput Graph Stat
Date Published2013

Large margin classifiers have been shown to be very useful in many applications. The Support Vector Machine is a canonical example of large margin classifiers. Despite their flexibility and ability in handling high dimensional data, many large margin classifiers have serious drawbacks when the data are noisy, especially when there are outliers in the data. In this paper, we propose a new weighted large margin classification technique. The weights are chosen adaptively with data. The proposed classifiers are shown to be robust to outliers and thus are able to produce more accurate classification results.

Alternate JournalJ Comput Graph Stat
Original PublicationAdaptively weighted large margin classifiers.
PubMed ID24363545
PubMed Central IDPMC3867158
Grant ListP01 CA142538 / CA / NCI NIH HHS / United States
R01 CA149569 / CA / NCI NIH HHS / United States