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- W2386491463 abstract "This paper proposes a learning strategy of SVM used to large training set. First authors train an initial classifier with a small training set, then prune the large training set with the initial classifier to obtain a small reduction set. Training with the reduction set, final classifier is obtained. Experiments show that the learning strategy not only reduces the cost greatly but also obtains a classifier that has the same accuracy as(even better than) the classifier obtained by training large set directly. In addition, speed of classification is greatly improved." @default.
- W2386491463 created "2016-06-24" @default.
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- W2386491463 date "2004-01-01" @default.
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- W2386491463 title "A Learning Strategy of SVM Used to Large Training Set" @default.
- W2386491463 hasPublicationYear "2004" @default.
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