A Fast Shapelet Discovery Algorithm Based on Important Data Points
A Fast Shapelet Discovery Algorithm Based on Important Data Points
复制标题
一种基于重要数据点的快速Shapelet发现算法
DOI：
10.4018/ijwsr.2017040104
复制
发表时间：
2017-04-01
影响因子：
1.1
通讯作者：
Wu, Lei
中科院分区：
文献类型：
--
作者：
Ji, Cun;Zhao, Chao;Wu, Lei
在过去的十年里，时间序列分类TSC引起了人们极大的兴趣。形状是时间序列的一个片段，它可以表示时间序列的类特征。基于Shaplet的分类器是可解释的，更准确，更快。然而，寻找Shaplet所需的时间是巨大的。本文将提出一种基于重要数据点IdP的Shapelet FS快速发现算法。首先，该算法将识别国内流离失所者。接下来，包含一个或多个IDP的子序列将被选为候选形状。最后，将选出最好的Shaplet。实验结果表明，该算法在保持分类准确率不变的情况下，将形状集发现时间减少了约14.0%。
Time series classification TSC has attracted significant interest over the past decade. A shapelet is one fragment of a time series that can represent class characteristics of the time series. A classifier based on shapelets is interpretable, more accurate, and faster. However, the time it takes to find shapelets is enormous. This article will propose a fast shapelet FS discovery algorithm based on important data points IDPs. First, the algorithm will identify IDPs. Next, the subsequence containing one or more IDPs will be selected as a candidate shapelet. Finally, the best shapelets will be selected. Results will show that the proposed algorithm reduces the shapelet discovery time by approximately 14.0% while maintaining the same level of classification accuracy rates.