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Parallel Predicting Algorithm Based on Support Vector Regression Machine

机译:基于支持向量回归机的并行预测算法

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摘要

Using support vector regression machine to predict a large-scale dataset, which will take a long time. In order to solve the problem, this paper proposes a parallel predicting algorithm based on sample separation, and introduces the design and implementation of the algorithm. The performance of the algorithm has been evaluated and analyzed with KDD99 dataset on the ZQ3000 cluster. Experimental results show that the algorithm not only effectively reduces the time of predicting dataset, but also keeps high accuracy rate.
机译:使用支持向量回归机预测大规模数据集,这将需要很长时间。为了解决这一问题,本文提出了一种基于样本分离的并行预测算法,并介绍了该算法的设计与实现。该算法的性能已通过ZQ3000集群上的KDD99数据集进行了评估和分析。实验结果表明,该算法不仅有效地减少了数据集的预测时间,而且保持了较高的准确率。

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