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Titlebook: Intelligent Data Engineering and Automated Learning - IDEAL 2006; 7th International Co Emilio Corchado,Hujun Yin,Colin Fyfe Conference proc

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A Fast Algorithm for Relevance Vector Machine algorithm. The verification using one group of toy data sets and three benchmark data sets shows that the proposed fast relevance vector machine is able to speed up the training time significantly while maintaining the model performance including testing accuracy, model robustness and model sparseness.
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Speed-Up LOO-CV with SVM Classifiermethod which uses modified initialization of Sequential Minimal Optimization (SMO) algorithm for SVM to speed-up LOO-CV. Moreover, when SMO’s stopping criterion is changed with our adaptive method, experimental results show that speed-up of LOO-CV is greatly increased while LOO error estimation is very close to exact LOO error estimation.
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