计算机科学 ›› 2018, Vol. 45 ›› Issue (2): 291-296.doi: 10.11896/j.issn.1002-137X.2018.02.050
马超红,翁小清
MA Chao-hong and WENG Xiao-qing
摘要： 在时间序列数据挖掘领域,时间序列的早期分类越来越受到人们的重视,由于时间序列的长度(也称为维数)较大,在早期分类的实际应用中选择合适的维数约简方法非常重要,因此提出一种基于分段聚合近似(PAA)的时间序列早期分类方法。首先运用PAA对时间序列样本进行维数约简,然后在低维空间对样本进行早期分类,在43个时间序列数据集上的实验结果表明, 所提方法 在准确率、早期性、可靠性等方面优于已有方法。
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