A Fast Shapelet Discovery Algorithm Based on Important Data Points

作者：Ji, Cun^*; Zhao, Chao; Pan, Li; Liu, Shijun; Yang, Chenglei; Wu, Lei

来源：International Journal of Web Services Research, 2017, 14(2): 67-80.

DOI：10.4018/IJWSR.2017040104

• Classification
• Data Mining
• Important Data Points
• Internet of Things
• Shapelet
• Time Series Data

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.

• 出版日期2017-6
• 单位山东大学