Boosting SVM classifiers by ensemble

10 years 8 months ago
Boosting SVM classifiers by ensemble
By far, the support vector machines (SVM) achieve the state-of-theart performance for the text classification (TC) tasks. Due to the complexity of the TC problems, it becomes a challenge to systematically develop classifiers with better performance. We try to attack this problem by ensemble methods, which are often used for boosting weak classifiers, such as decision tree, neural networks, etc., and whether they are effective for strong classifiers is not clear. Categories and Subject Descriptors H.3.3 [Information Storage and Retrieval]: Information Search and Retrieval; I.5.2 [Pattern Recognition]: Design Methodology General Terms Algorithms, Experimentation Keywords Classifier design and evaluation, Information filtering, Machine learning, Neural nets, Text processing
Yan-Shi Dong, Ke-Song Han
Added 22 Nov 2009
Updated 22 Nov 2009
Type Conference
Year 2005
Where WWW
Authors Yan-Shi Dong, Ke-Song Han
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