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- W2338678269 abstract "SVM is an effective method for learning the classification knowledge from massive data, especially in the situation of high cost in getting labeled classical examples. Based on the analysis of tow parallel proximal support vector machine (PSVM) algorithm-model algorithm and Cascade SVMs algorithm, an improved parallel support vector machine classification algorithm (IPSVM) was proposed, based on the Cascade SVMs. In the IPSVM, the circulating feedback between support vector sets is used to improve classifier performance and is adjusted to save training time of classifier based on the feedback type in Cascade SVMs. The IPSVM is especially suitable to the case of large-scale training set and large number of support vectors. The experimental results indicate that the new method works well in precision and recall rate in the condition that the speeds of classification increase remarkably." @default.
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- W2338678269 date "2012-05-18" @default.
- W2338678269 modified "2023-09-22" @default.
- W2338678269 title "An Improved Parallel SVM Algorithm for Chinese Text Classification" @default.
- W2338678269 doi "https://doi.org/10.1109/icetce.2012.67" @default.
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